CN108540773A - A kind of monitoring method, device, system and Cloud Server - Google Patents
A kind of monitoring method, device, system and Cloud Server Download PDFInfo
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Abstract
A kind of monitoring method, device, system and Cloud Server provided by the invention judge whether there is object of which movement in the target zone according to the image collected information in predetermined period；When being determined with object of which movement, the recording function for starting image capture device is recorded a video, and starts the temperature and environment temperature of infrared radiation thermometer detection moving object；According to the image of the temperature of the moving object, environment temperature and the moving object, the type of the moving object is identified；The video file of the information of the moving object and the moving object is uploaded to Cloud Server, makes the Cloud Server that the video file of the information of the moving object and the moving object is sent to user terminal.The monitoring for invading non-human situation is realized, user is made to know the sanitary conditions of local environment.
Description
Technical Field
The invention relates to the technical field of monitoring, in particular to a monitoring method, a monitoring device, a monitoring system and a cloud server.
Background
The human living environment may have harmful animals, and the more common harmful animals include mice, flies, cockroaches, termites, and the like. These pests do not harm the safety of people at all times and are unpleasant, and people must take measures to remove the pests in the room to obtain a good living environment.
One first knows whether pests are present in the room, and which pests are present, before removing them. However, the vermin are generally hidden when people move, and people have difficulty in monitoring the vermin.
At present, people generally adopt monitoring systems to monitor indoor and outdoor environments, but most of the existing safety monitoring systems take human beings as monitoring targets and pay attention to invasion except the human beings.
Disclosure of Invention
In view of the above, the present invention is proposed to provide a monitoring method, apparatus, system and cloud server that overcome the above problems or at least partially solve the above problems.
In order to achieve the above purpose, the invention provides the following specific technical scheme:
a method of monitoring, comprising:
controlling an image acquisition device to acquire image information within a target range;
judging whether an object moves in the target range according to image information acquired in a preset period;
when the object is judged to move, starting a video recording function of the image acquisition equipment for recording, and acquiring a feature value of a preset type;
judging whether the moving object is a target animal or not according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal, wherein the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment;
and when the moving object is a target animal, uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
Preferably, the determining whether there is an object moving in the target range according to the image information collected in the preset period includes:
counting the macro block motion vector in each frame of image information collected in a preset period to obtain the maximum value of the macro block motion vector in each frame of image information;
calculating the weighted average value of the maximum value of the macro block motion vector in each frame of image information to obtain the image motion vector value of the preset period;
judging whether the image motion vector value of the preset period exceeds a preset value or not;
if yes, determining that an object moves in the target range;
if not, determining that no object moves in the target range.
Preferably, the image acquisition device comprises a camera and a depth camera;
the control image acquisition equipment acquires image information in a target range, and specifically comprises the following steps:
controlling the camera to acquire image information within a target range;
the starting of the video recording function of the image acquisition equipment for video recording specifically comprises the following steps:
and starting the video recording functions of the camera and the depth camera to record.
Preferably, the acquiring the feature values of the preset type includes:
and starting an infrared thermometer to acquire the ambient temperature and the temperature of the moving object.
Preferably, the determining whether the moving object is a target animal according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal includes:
traversing pre-stored body temperature range data tables of different target animals and pre-stored environment temperature range data tables of different target animals by taking the collected environment temperature and the temperature of the moving object as query conditions, and determining at least one suspected target animal corresponding to the moving object;
calling a neural network image recognition model corresponding to each suspected target animal stored by the cloud server, and taking the image of the moving object as input data to obtain a recognition result of the neural network image recognition model corresponding to each suspected target animal;
and judging whether the moving object is a target animal or not according to the identification result of the neural network image identification model corresponding to each suspected target animal, and determining the type of the target animal of the moving object when the moving object is the target animal.
A monitoring method is applied to a cloud server, and comprises the following steps:
receiving the type information of the moving object and the video file of the moving object sent by the monitoring device;
storing the category information of the moving object and the video file of the moving object;
and transmitting the category information of the moving object and the video file of the moving object to a user terminal.
Preferably, the cloud server stores neural network image recognition models corresponding to different types of target animals in advance,
the method further comprises the following steps:
judging whether feedback information of the user terminal is received or not within preset time;
if so, judging whether the type identification of the moving object is correct or not according to the feedback information;
if the target animal neural network image recognition model is correct, storing the image of the moving object as a correct training sample of the corresponding target animal neural network image recognition model;
if not, storing the image of the moving object as an error training sample of a corresponding target animal neural network image recognition model;
and if not, determining that the type of the moving object is correctly identified, and storing the image of the moving object as a correct training sample of a corresponding target animal neural network image identification model.
Preferably, the method further comprises:
and respectively counting the occurrence time, frequency and frequency of each target animal in a preset counting period, generating a counting report according to a counting result in the preset counting period, and pushing the counting report to the user terminal.
A monitoring device, comprising:
the control unit is used for controlling the image acquisition equipment to acquire image information within a target range;
the judging unit is used for judging whether an object moves in the target range according to the image information collected in a preset period;
the starting unit is used for starting the video recording function of the image acquisition equipment to record video and acquiring a preset type of characteristic value when the object motion is judged;
the identification unit is used for judging whether the moving object is a target animal or not according to the preset type of characteristic value and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal, wherein the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment;
and the uploading unit is used for uploading the type information of the moving object and the video file of the moving object to a cloud server when the moving object is a target animal, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
A cloud server, comprising:
the receiving unit is used for receiving the type information of the moving object and the video file of the moving object sent by the monitoring device;
the storage unit is used for storing the category information of the moving object and the video file of the moving object;
and the sending unit is used for sending the category information of the moving object and the video recording file of the moving object to the user terminal.
A monitoring system, comprising:
the system comprises a processor, image acquisition equipment, an infrared thermometer, the cloud server and a user terminal;
the processor comprises the monitoring device.
Preferably, the monitoring system further comprises: the device comprises a photoresistor, double optical filters and an infrared light supplement lamp;
the photoresistor is used for detecting the light intensity;
the processor is further used for controlling the dual filters to switch to a night mode when the light intensity is lower than a threshold value, and controlling the dual filters to switch to a day mode when the light intensity is not lower than the threshold value;
and the infrared light supplement lamp is used for emitting infrared light to illuminate in a night mode.
By means of the technical scheme, the monitoring method, the monitoring device, the monitoring system and the cloud server provided by the invention judge whether an object moves in the target range according to the image information acquired in the preset period; when the object is judged to move, starting a video recording function of the image acquisition equipment for recording video, and starting an infrared thermometer to detect the temperature of the moving object and the ambient temperature; identifying the type of the moving object according to the temperature of the moving object, the ambient temperature and the image of the moving object; and uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal. The system realizes the monitoring of the non-human invasion condition and enables the user to know the sanitation condition of the environment.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart of a monitoring method disclosed in an embodiment of the present invention;
FIG. 2 is a flow chart of a method for determining motion of an object according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for identifying a target animal according to an embodiment of the present invention;
FIG. 4 is a flow chart of another monitoring method disclosed in the embodiments of the present invention;
FIG. 5 is a flow chart of another monitoring method disclosed in the embodiments of the present invention;
FIG. 6 is a schematic structural diagram of a monitoring device according to an embodiment of the disclosure;
FIG. 7 is a schematic diagram of a cloud server structure according to an embodiment of the present disclosure;
FIG. 8 is a schematic diagram of a monitoring system according to an embodiment of the present invention;
fig. 9 shows a schematic structural diagram of another monitoring system disclosed in the embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Referring to fig. 1, the present embodiment discloses a monitoring method, which specifically includes the following steps:
s101: controlling an image acquisition device to acquire image information within a target range;
the target range is a view angle area of the image acquisition device.
The device for acquiring the image information in the target range in the image acquisition device can be a camera and the like.
S102: judging whether an object moves in the target range according to image information acquired in a preset period; if yes, go to step S103;
the preset period is a preset time interval value, such as 1 second, 2 seconds, etc., and the invention is not limited thereto. It can be understood that, in each preset period, whether an object moves in the target range is judged according to the acquired image information.
If not, S102 is continuously executed, and whether an object moves in the target range is judged in the next preset period according to the image information acquired in the next preset period.
Specifically, the determination of whether there is an object moving in the image may be any one of the existing methods, preferably, referring to fig. 2, the specific implementation process of S102 is as follows:
s201: counting the macro block motion vector in each frame of image information collected in a preset period to obtain the maximum value of the macro block motion vector in each frame of image information;
s202: calculating the weighted average value of the maximum value of the macro block motion vector in each frame of image information to obtain the image motion vector value of the preset period;
s203: judging whether the image motion vector value of the preset period exceeds a preset value or not; if yes, executing S204, otherwise, executing S205;
s204: determining that there is object motion within the target range;
s205: and judging that no object moves in the target range.
It should be noted that, the weight of each frame of image collected in the preset period is the same, and the calculation formula of the image motion vector value of the preset period is as follows:
y＝(ax1+ax2+...+axn)/n
wherein,yis the value of the image motion vector of a preset period, a is the weight, xnThe maximum value of the macro block motion vector in the nth frame of image information is shown, and n is the total frame number of the images in the preset period.
S103: starting a video recording function of the image acquisition equipment to record video, and acquiring a preset type of characteristic value;
preferably, the image acquisition device comprises a camera and a depth camera.
The starting of the video recording function of the image acquisition equipment for video recording specifically comprises the following steps:
and starting the video recording functions of the camera and the depth camera to record.
It can be understood that the image acquired by the camera has higher resolution but cannot acquire the depth information of the image, the image acquired by the depth camera has lower resolution but can acquire the depth information of the image, and meanwhile, the acquired image simultaneously meets the requirements of resolution and depth information by utilizing the images acquired by the camera and the depth camera.
Meanwhile, the neural network image recognition model corresponding to each target animal takes the RGB image and the depth image of the corresponding target animal as training samples, so that the trained neural network image recognition model can use the RGB image acquired by the camera and the depth image acquired by the depth camera as input data to judge whether a moving object in the image is the target animal corresponding to the neural network image recognition model, and the input data and the training samples simultaneously meet the requirements on the resolution ratio and the depth information of the image, so that the recognition accuracy of the moving object is improved.
Note that the video recording is stopped when the type of the moving object is identified.
Preferably, the acquiring the feature values of the preset type includes:
and starting an infrared thermometer to acquire the ambient temperature and the temperature of the moving object.
S104: judging whether the moving object is a target animal or not according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal;
the target animal is a preset animal, can be set as harmful animals such as cockroaches and mice when the embodiment is applied to monitoring environmental sanitation, and can be set as pets such as cats and dogs when the embodiment is applied to monitoring pets. It is to be understood that the vermin and pets are merely alternative examples of target animals, and the invention is not limited thereto.
The image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment. It will be appreciated that each frame of the video file is an image of a moving object.
Specifically, referring to fig. 3, the specific execution process of S104 is as follows:
s301: traversing pre-stored body temperature range data tables of different target animals and environment temperature ranges of the different target animals by taking the collected environment temperature and the temperature of the moving object as query conditions, and determining at least one suspected target animal corresponding to the moving object;
for example, if the body temperature of the mouse is 37-38 ℃ and the temperature of the moving object is not in the range, image recognition of the mouse does not need to be started; the cockroach is a variable-temperature animal, the moving environment temperature is more than 15 ℃, and the environment temperature is less than 15 ℃, so that the image recognition of the cockroach is not started; the fly is a variable-temperature animal, the activity temperature is above 10 ℃, and if the environment temperature is below 10 ℃, the image recognition of the fly is not started.
The embodiment provides a body temperature range of various target animals and an environment temperature range of the target animals, and eliminates the target animals which do not meet the conditions according to the temperature and the environment temperature of the moving object to obtain at least one suspected target animal species.
S302: calling a neural network image recognition model corresponding to each suspected target animal stored by the cloud server, and taking the image of the moving object as input data to obtain a recognition result of the neural network image recognition model corresponding to each suspected target animal;
s303: and judging whether the moving object is a target animal or not according to the identification result of the neural network image identification model corresponding to each suspected target animal, and determining the type of the target animal of the moving object when the moving object is the target animal. (ii) a
It should be noted that the cloud server stores the neural network image recognition model corresponding to each target animal. The neural network image recognition model takes the RGB image and the depth image of the corresponding target animal as training samples. The neural network image recognition model corresponding to each target animal can be obtained by training a convolutional neural network model or a deep neural network model.
In this embodiment, a neural network image recognition model of multiple target animals is provided, and for each suspected target animal, when it is determined whether the moving object is the suspected target animal, the neural network image recognition model corresponding to the suspected target animal is called, the image of the moving object is used as input data, and the output data is a recognition result, that is, whether the moving object is the suspected target animal. It can be understood that, when the recognition result of the neural network image recognition model corresponding to each suspected target animal is negative, the moving object is not the target animal; and when the recognition result of the neural network image recognition model corresponding to only one suspected target animal in the recognition results is yes, taking the suspected target animal as the target animal type of the moving object.
S105: and when the moving object is a target animal, uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
The user terminal can be a smart phone, an IPad, a tablet computer, a notebook computer and the like.
According to the monitoring method disclosed by the embodiment, whether an object moves in the target range is judged according to image information collected in a preset period; when the object is judged to move, starting a video recording function of the image acquisition equipment for recording video, and starting an infrared thermometer to detect the temperature of the moving object and the ambient temperature; identifying the type of the moving object according to the temperature of the moving object, the ambient temperature and the image of the moving object; and uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal. The system realizes the monitoring of the non-human invasion condition and enables the user to know the sanitation condition of the environment.
Referring to fig. 4, the present embodiment discloses another monitoring method applied to a cloud server, which specifically includes the following steps:
s401: receiving the type information of the moving object and the video file of the moving object sent by the monitoring device;
s402: storing the category information of the moving object and the video file of the moving object;
s403: and transmitting the category information of the moving object and the video file of the moving object to a user terminal.
In the monitoring method disclosed in this embodiment, the cloud server receives and stores the type information of the moving object and the video file of the moving object sent by the monitoring device, and sends the type information of the moving object and the video file of the moving object to the user terminal. The storage pressure of the monitoring device is relieved, the type information of the moving object and the video file of the moving object, which are identified by the monitoring device, are sent to the user terminal, and a user can know the sanitation condition of the environment where the user is located conveniently.
Referring to fig. 5, in another monitoring method disclosed in this embodiment, the cloud server stores in advance neural network image recognition models corresponding to different types of target animals, and the monitoring method specifically includes:
s501: receiving the type information of the moving object and the video file of the moving object sent by the monitoring device;
s502: storing the category information of the moving object and the video file of the moving object;
s503: transmitting the category information of the moving object and the video file of the moving object to a user terminal;
s504: judging whether feedback information of the user terminal is received or not within preset time;
if yes, executing S505, and if not, executing S506;
it should be noted that the preset time is a preset period of time, and if the feedback information of the user terminal is not received within the preset time, the user is defaulted to approve the identification result of the monitoring device.
S505: judging whether the type identification of the moving object is correct or not according to the feedback information; if correct, execute S507, if incorrect, execute S508;
s507: storing the image of the moving object as a correct training sample of a corresponding target animal neural network image recognition model;
s508: storing the image of the moving object as an error training sample of a corresponding target animal neural network image recognition model;
s506: and determining that the type of the moving object is correctly identified, and storing the image of the moving object as a correct training sample of a corresponding target animal neural network image identification model.
The recognition accuracy can be improved through the result fed back by the user, for example, the processor recognizes the domestic cat as a mouse, and after the user feeds back, the video file of the domestic cat is removed from the training sample of the mouse, or the video file of the domestic cat is added into the training sample of the domestic cat, so that the recognition accuracy of the processor is improved.
Preferably, the method further comprises:
and when the type of the moving object is correctly identified, pushing information of the processing target animal corresponding to the identified type of the moving object to the user terminal through a pre-accessed advertisement system for processing the target animal. The information can be advertisements, contact information of related properties, links of product purchase pages of processing target animals of a third-party platform, and the like.
For example, when the cloud server receives that the moving object sent by the processor is a mouse or when the cloud server determines that the moving object is a mouse according to the feedback of the user terminal, an instruction carrying the mouse is sent to the advertisement system, and when the mouse-killing advertisement fed back by the advertisement system is received, the mouse-killing advertisement is pushed to the user terminal.
Preferably, the method further comprises:
and respectively counting the occurrence time, frequency and frequency of each target animal in a preset counting period, generating a counting report according to a counting result in the preset counting period, and pushing the counting report to the user terminal.
The preset statistical period can be one day, one week, one month, one year and the like, and the statistical function of the cloud server can enable a user to know the sanitation state of the monitored environment in each statistical period.
Referring to fig. 6, a monitoring method disclosed based on the above embodiment correspondingly discloses a monitoring device, which specifically includes:
the control unit 601 is used for controlling the image acquisition equipment to acquire image information within a target range;
a determining unit 602, configured to determine whether an object moves within the target range according to image information acquired in a preset period;
a starting unit 603, configured to start a video recording function of the image acquisition device to record a video and acquire a feature value of a preset type when it is determined that an object moves;
the identifying unit 604 is configured to determine whether the moving object is a target animal according to the feature value of the preset type and the image of the moving object, and identify a target animal type of the moving object when the moving object is the target animal, where the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition device;
a sending unit 605, configured to upload, when the moving object is a target animal, the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
According to the monitoring device disclosed by the embodiment, whether an object moves in a target range is judged according to image information collected in a preset period; when the object is judged to move, starting a video recording function of the image acquisition equipment for recording video, and starting an infrared thermometer to detect the temperature of the moving object and the ambient temperature; identifying the type of the moving object according to the temperature of the moving object, the ambient temperature and the image of the moving object; and uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal. The system realizes the monitoring of the non-human invasion condition and enables the user to know the sanitation condition of the environment.
Referring to fig. 7, the embodiment correspondingly discloses a cloud server based on the monitoring method disclosed in the foregoing embodiment, which includes:
a receiving unit 701, configured to receive the type information of the moving object and the video file of the moving object sent by the monitoring device;
a storage unit 702, configured to store category information of the moving object and a video file of the moving object;
a sending unit 703, configured to send the category information of the moving object and the video recording file of the moving object to a user terminal.
The cloud server disclosed in this embodiment receives and stores the type information of the moving object and the video file of the moving object sent by the monitoring device, and sends the type information of the moving object and the video file of the moving object to the user terminal. The storage pressure of the monitoring device is relieved, the type information of the moving object and the video file of the moving object, which are identified by the monitoring device, are sent to the user terminal, and a user can know the sanitation condition of the environment where the user is located conveniently.
Referring to fig. 8, the monitoring apparatus and the cloud server disclosed in the above embodiments disclose a monitoring system, which includes: the system comprises image acquisition equipment 801, an infrared thermometer 802, a processor 803, a cloud server 804 and a user terminal 805 disclosed by the above embodiments; the processor 803 includes the monitoring device disclosed in the above embodiments.
The image acquisition device 801 is configured to acquire image information within a target range. And video recording when the processor 803 detects that there is movement of an object within the target range.
The infrared thermometer 502 is used for detecting the temperature of the moving object and the ambient temperature.
It should be noted that the data acquired by the image acquisition device 801 and the infrared thermometer 802 need to be sent to the processor 803.
The user terminal 805 may be a smart phone, an iPad, a tablet computer, a notebook computer, or the like.
Preferably, the monitoring system further comprises a cradle head, the cradle head is a base of the image acquisition device 801, the cradle head comprises a horizontal or vertical rotation device for controlling the image acquisition device 801 to rotate horizontally or vertically so as to align with the monitoring area, and the cradle head is controlled to rotate by the processor.
According to the monitoring system disclosed by the embodiment, whether an object moves in the target range is judged according to the image information collected in the preset period; when the object is judged to move, starting a video recording function of the image acquisition equipment for recording video, and starting an infrared thermometer to detect the temperature of the moving object and the ambient temperature; identifying the type of the moving object according to the temperature of the moving object, the ambient temperature and the image of the moving object; and transmitting the category information of the moving object and the video file of the moving object to a user terminal. The system realizes the monitoring of the non-human invasion condition and enables the user to know the sanitation condition of the environment.
Referring to fig. 9, the monitoring system disclosed based on the above embodiment further includes: a photoresistor 806, a double-optical filter 807 and an infrared light supplement lamp 808;
the photoresistor 806 is used for detecting the light intensity;
the photoresistor 806 is connected with the single chip microcomputer through an I2C interface, and the single chip microcomputer is connected with the processor 803 through a serial/parallel/SPI interface.
The processor 803 is further configured to switch to the night mode by controlling the dual filters 807 when the light intensity is below a threshold value, and to switch to the day mode by controlling the dual filters 807 when the light intensity is not below the threshold value;
the dual filters 807 serve to transmit infrared light at all times in the night mode and filter infrared light in the day mode.
And the infrared light supplement lamp 808 is used for emitting infrared light to illuminate in a night mode.
The monitoring system disclosed by the embodiment realizes monitoring and identification of the target animal when light is weak through the photoresistor, the double optical filters and the infrared light supplementing lamp.
The monitoring device comprises a memory, the control unit, the judgment unit, the starting unit, the identification unit, the sending unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more, and the identification accuracy of the target animal is improved by adjusting the kernel parameters.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
An embodiment of the present invention provides a storage medium on which a program is stored, the program implementing the monitoring method when executed by a processor.
The embodiment of the invention provides a processor, which is used for running a program, wherein the monitoring method is executed when the program runs:
controlling an image acquisition device to acquire image information within a target range;
judging whether an object moves in the target range according to image information acquired in a preset period;
when the object is judged to move, starting a video recording function of the image acquisition equipment for recording, and acquiring a feature value of a preset type;
judging whether the moving object is a target animal or not according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal, wherein the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment;
and when the moving object is a target animal, uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
Further, the step of judging whether an object moves in the target range according to the image information acquired in the preset period includes:
counting the macro block motion vector in each frame of image information collected in a preset period to obtain the maximum value of the macro block motion vector in each frame of image information;
calculating the weighted average value of the maximum value of the macro block motion vector in each frame of image information to obtain the image motion vector value of the preset period;
judging whether the image motion vector value of the preset period exceeds a preset value or not;
if yes, determining that an object moves in the target range;
if not, determining that no object moves in the target range.
Further, the image acquisition device comprises a camera and a depth camera;
the control image acquisition equipment acquires image information in a target range, and specifically comprises the following steps:
controlling the camera to acquire image information within a target range;
the starting of the video recording function of the image acquisition equipment for video recording specifically comprises the following steps:
and starting the video recording functions of the camera and the depth camera to record.
Further, the collecting the feature values of the preset types includes:
and starting an infrared thermometer to acquire the ambient temperature and the temperature of the moving object.
Further, the determining whether the moving object is a target animal according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal includes:
traversing pre-stored body temperature range data tables of different target animals and pre-stored environment temperature range data tables of different target animals by taking the collected environment temperature and the temperature of the moving object as query conditions, and determining at least one suspected target animal corresponding to the moving object;
calling a neural network image recognition model corresponding to each suspected target animal stored by the cloud server, and taking the image of the moving object as input data to obtain a recognition result of the neural network image recognition model corresponding to each suspected target animal;
and judging whether the moving object is a target animal or not according to the identification result of the neural network image identification model corresponding to each suspected target animal, and determining the type of the target animal of the moving object when the moving object is the target animal.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device:
controlling an image acquisition device to acquire image information within a target range;
judging whether an object moves in the target range according to image information acquired in a preset period;
when the object is judged to move, starting a video recording function of the image acquisition equipment for recording, and acquiring a feature value of a preset type;
judging whether the moving object is a target animal or not according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal, wherein the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment;
and when the moving object is a target animal, uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
Further, the step of judging whether an object moves in the target range according to the image information acquired in the preset period includes:
counting the macro block motion vector in each frame of image information collected in a preset period to obtain the maximum value of the macro block motion vector in each frame of image information;
calculating the weighted average value of the maximum value of the macro block motion vector in each frame of image information to obtain the image motion vector value of the preset period;
judging whether the image motion vector value of the preset period exceeds a preset value or not;
if yes, determining that an object moves in the target range;
if not, determining that no object moves in the target range.
Further, the image acquisition device comprises a camera and a depth camera;
the control image acquisition equipment acquires image information in a target range, and specifically comprises the following steps:
controlling the camera to acquire image information within a target range;
the starting of the video recording function of the image acquisition equipment for video recording specifically comprises the following steps:
and starting the video recording functions of the camera and the depth camera to record.
Further, the collecting the feature values of the preset types includes:
and starting an infrared thermometer to acquire the ambient temperature and the temperature of the moving object.
Further, the determining whether the moving object is a target animal according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal includes:
traversing pre-stored body temperature range data tables of different target animals and pre-stored environment temperature range data tables of different target animals by taking the collected environment temperature and the temperature of the moving object as query conditions, and determining at least one suspected target animal corresponding to the moving object;
calling a neural network image recognition model corresponding to each suspected target animal stored by the cloud server, and taking the image of the moving object as input data to obtain a recognition result of the neural network image recognition model corresponding to each suspected target animal;
and judging whether the moving object is a target animal or not according to the identification result of the neural network image identification model corresponding to each suspected target animal, and determining the type of the target animal of the moving object when the moving object is the target animal.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (12)
1. A method of monitoring, comprising:
controlling an image acquisition device to acquire image information within a target range;
judging whether an object moves in the target range according to image information acquired in a preset period;
when the object is judged to move, starting a video recording function of the image acquisition equipment for recording, and acquiring a feature value of a preset type;
judging whether the moving object is a target animal or not according to the feature value of the preset type and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal, wherein the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment;
and when the moving object is a target animal, uploading the type information of the moving object and the video file of the moving object to a cloud server, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
2. The method according to claim 1, wherein the determining whether there is an object moving in the target range according to the image information collected in the preset period comprises:
counting the macro block motion vector in each frame of image information collected in a preset period to obtain the maximum value of the macro block motion vector in each frame of image information;
calculating the weighted average value of the maximum value of the macro block motion vector in each frame of image information to obtain the image motion vector value of the preset period;
judging whether the image motion vector value of the preset period exceeds a preset value or not;
if yes, determining that an object moves in the target range;
if not, determining that no object moves in the target range.
3. The method of claim 1, wherein the image capture device comprises a camera and a depth camera;
the control image acquisition equipment acquires image information in a target range, and specifically comprises the following steps:
controlling the camera to acquire image information within a target range;
the starting of the video recording function of the image acquisition equipment for video recording specifically comprises the following steps:
and starting the video recording functions of the camera and the depth camera to record.
4. The method of claim 1, wherein the collecting the feature values of the preset type comprises:
and starting an infrared thermometer to acquire the ambient temperature and the temperature of the moving object.
5. The method of claim 4, wherein the determining whether the moving object is a target animal according to the preset type of feature value and the image of the moving object, and identifying the target animal type of the moving object when the moving object is the target animal comprises:
traversing pre-stored body temperature range data tables of different target animals and pre-stored environment temperature range data tables of different target animals by taking the collected environment temperature and the temperature of the moving object as query conditions, and determining at least one suspected target animal corresponding to the moving object;
calling a neural network image recognition model corresponding to each suspected target animal stored by the cloud server, and taking the image of the moving object as input data to obtain a recognition result of the neural network image recognition model corresponding to each suspected target animal;
and judging whether the moving object is a target animal or not according to the identification result of the neural network image identification model corresponding to each suspected target animal, and determining the type of the target animal of the moving object when the moving object is the target animal.
6. A monitoring method is applied to a cloud server, and comprises the following steps:
receiving the type information of the moving object and the video file of the moving object sent by the monitoring device;
storing the category information of the moving object and the video file of the moving object;
and transmitting the category information of the moving object and the video file of the moving object to a user terminal.
7. The method according to claim 6, wherein the cloud server stores neural network image recognition models corresponding to different types of target animals in advance,
the method further comprises the following steps:
judging whether feedback information of the user terminal is received or not within preset time;
if so, judging whether the type identification of the moving object is correct or not according to the feedback information;
if the target animal neural network image recognition model is correct, storing the image of the moving object as a correct training sample of the corresponding target animal neural network image recognition model;
if not, storing the image of the moving object as an error training sample of a corresponding target animal neural network image recognition model;
and if not, determining that the type of the moving object is correctly identified, and storing the image of the moving object as a correct training sample of a corresponding target animal neural network image identification model.
8. The method of claim 6, further comprising:
and respectively counting the occurrence time, frequency and frequency of each target animal in a preset counting period, generating a counting report according to a counting result in the preset counting period, and pushing the counting report to the user terminal.
9. A monitoring device, comprising:
the control unit is used for controlling the image acquisition equipment to acquire image information within a target range;
the judging unit is used for judging whether an object moves in the target range according to the image information collected in a preset period;
the starting unit is used for starting the video recording function of the image acquisition equipment to record video and acquiring a preset type of characteristic value when the object motion is judged;
the identification unit is used for judging whether the moving object is a target animal or not according to the preset type of characteristic value and the image of the moving object, and identifying the type of the target animal of the moving object when the moving object is the target animal, wherein the image of the moving object is derived from a video file obtained by video recording of the moving object by the image acquisition equipment;
and the uploading unit is used for uploading the type information of the moving object and the video file of the moving object to a cloud server when the moving object is a target animal, so that the cloud server sends the type information of the moving object and the video file of the moving object to a user terminal.
10. A cloud server, comprising:
the receiving unit is used for receiving the type information of the moving object and the video file of the moving object sent by the monitoring device;
the storage unit is used for storing the category information of the moving object and the video file of the moving object;
and the sending unit is used for sending the category information of the moving object and the video recording file of the moving object to the user terminal.
11. A monitoring system, comprising:
a processor, image acquisition equipment, an infrared thermometer, the cloud server of claim 10, and a user terminal;
the processor comprises the monitoring device of claim 9.
12. The monitoring system of claim 11, further comprising: the device comprises a photoresistor, double optical filters and an infrared light supplement lamp;
the photoresistor is used for detecting the light intensity;
the processor is further used for controlling the dual filters to switch to a night mode when the light intensity is lower than a threshold value, and controlling the dual filters to switch to a day mode when the light intensity is not lower than the threshold value;
and the infrared light supplement lamp is used for emitting infrared light to illuminate in a night mode.
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