CN104484651A - Dynamic portrait comparing method and system - Google Patents
Dynamic portrait comparing method and system Download PDFInfo
- Publication number
- CN104484651A CN104484651A CN201410763088.2A CN201410763088A CN104484651A CN 104484651 A CN104484651 A CN 104484651A CN 201410763088 A CN201410763088 A CN 201410763088A CN 104484651 A CN104484651 A CN 104484651A
- Authority
- CN
- China
- Prior art keywords
- video
- portrait
- information
- server
- database
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/197—Matching; Classification
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Ophthalmology & Optometry (AREA)
- Human Computer Interaction (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Image Analysis (AREA)
Abstract
The invention relates to the technical field of portrait comparison, in particular to a dynamic portrait comparing method which comprises the following steps: acquiring portrait videos of different network points by using a video acquisition device; compressing the portrait videos acquired at the network points to form a stream media video file by using a stream media server, and storing the stream media video file; accessing to the stream media server through a real-time video portrait comparison server so as to obtain a camera video for identifying portraits, performing image analysis, and comparing the image with portraits in a databank in real time; judging whether the similarity of the portraits meets the standard value or not, if the similarity of the portraits meets the standard value, checking the information of people in the databank. Through the adoption of the dynamic portrait comparing method, the dynamic video information can be relatively well acquired by using the stream media server, so that the portrait information can be further acquired from the video information, and portrait comparison can be executed; on the other hand, the portraits of the databank can be updated in time by using the stream media server and a databank updating server according to video logs and important events.
Description
Technical field
The present invention relates to portrait correlation technique field, particularly a kind of portrait dynamic contrast method and system.
Background technology
Can well identify piece identity by Identification of Images contrast, present stage, a lot of field all employed face recognition system, for identification to improve safety.But because the quantity of information of daily video is comparatively large, good collection cannot be accomplished; In addition, when carrying out Identification of Images contrast, need from database, extract portrait data, and the portrait data in database also need to upgrade timely and adjustment.
Chinese invention patent CN 102682283 A discloses a kind of dynamic face recognition system, comprise real-time interconnection monitoring recognition system, non real-time interconnected monitoring system and real-time interconnection monitoring application module system, real-time interconnection monitoring recognition system comprises comprehensive monitoring platform and application platform, the input end of comprehensive monitoring platform is connected with front end human image collecting server, comprehensive monitoring platform output terminal is connected with day net video monitoring site and social unit video monitoring site, the input end of application platform is connected with Identification of Images comparison server and background data base server, the output terminal of application platform is connected with portrait search comparison subsystem, data maintenance Query Subsystem and alarm center, background data base server input is connected with and identifies contrast portrait storehouse, Identification of Images comparison server is connected with front end human image collecting server.
Summary of the invention
The method and system of the portrait dynamic contrast that technical issues that need to address speed of the present invention is fast, comparative analysis is effective.
For solving above-mentioned technical matters, the invention discloses a kind of portrait dynamic contrast method, comprising the following steps,
Step S101: the portrait video being gathered each site by video acquisition device;
Step S102: form streaming media video file after the portrait video compress collected each site by streaming media server and store;
Step S103: video real-time portrait comparison server, by access stream media server, obtains the camera video of Identification of Images, carries out graphical analysis, carry out real-time comparison with portrait in database;
Step S104: judge whether similarity meets, if similarity meets, enters step S105; If similarity does not meet, enter step S106;
Step S105: personal information inquiry in database;
Step S106: terminate.
Further, described step S103 is further comprising the steps of:
Step S1031: video acquisition, video real-time portrait comparison server, by access stream media server, obtains the camera video for Identification of Images;
Step S1032: face extraction, obtains corresponding facial image from the camera video that step S1031 obtains;
Step S1033: feature extraction, obtains the face characteristic of corresponding site from the facial image obtained;
Step S1034: similarity comparison, carries out similarity comparison by facial image feature in above-mentioned face characteristic and database.
Further, in described step S102, files in stream media also upgrades for database figure information, comprises the following steps:
S201: video information stores, the video data information of files in stream media is stored in video information storage unit, and zone bit setting is carried out to video information storage unit, then the scratchpad area (SPA) of database update server is stored in, described sign position setting comprises unique sign index of the transmit leg of portrait video, and all transmit legs are all with unique sign index that the respective take over party as portrait video is general within the scope of data delivery area, such transmit leg just exports the instruction of claimant as video by unique sign index convection media server of the transmit leg with portrait video obtained, described claimant includes the unique sign index with the transmit leg of portrait video as the instruction of video,
S202: information sifting weighting, by being added with the video information storage unit of zone bit according to significance level weighting, then screens summation of weighted bits numerical value;
S203: figure information obtains, the video data information in the video information storage unit stay screening carries out face extraction and feature extraction, obtains figure information;
S204: figure information stores, and the figure information of acquisition is put into figure information storage unit by database update server;
S205: database figure information upgrades, and figure information storage unit in database update server is arranged new zone bit, then the figure information storage unit being added with zone bit is updated in database.
Further, the zone bit of described step S205 figure information storage unit sets according to the qualitative classification of figure information.
The invention still further relates to a kind of portrait dynamic contrast system, comprise each site video signal acquisition device, described video signal acquisition device is connected with streaming media server, described streaming media server respectively portrait comparison server real-time with video is connected with database update server, described video real-time portrait comparison server, database update server are all connected with database, and described video real-time portrait comparison server is connected with application platform.
Further, described video acquisition device is divided into channel-style camera head and panorama camera device according to the difference of different position and angle.
After adopting said method and structure, the present invention can better obtain dynamic video information by arranging streaming media server, thus from video information, obtains figure information further, carries out portrait comparison; On the other hand, can be upgraded in time to database portrait according to video daily record and critical event situation by streaming media server and database update server.
Accompanying drawing explanation
Below in conjunction with the drawings and specific embodiments to being originally described in further detail.
Fig. 1 a is the process flow diagram of the present inventor as dynamic contrast method.
Fig. 1 b is the process flow diagram that database figure information of the present invention upgrades.
Fig. 2 is the structured flowchart of the present inventor as dynamic contrast system.
Fig. 3 a is the structural representation of video information storage unit of the present invention.
Fig. 3 b is the structural representation of database purchase of the present invention.
In figure: 1 is video signal acquisition device, 2 is streaming media server, and 3 is video real-time portrait comparison server, and 4 is database, and 5 is database update server, and 6 is application platform, and 7 is video information storage unit
401 is portrait information memory cell, and 402 is data bit, and 403 is zone bit
701 is data bit, and 702 is summation of weighted bits, and 703 is zone bit
Embodiment
As shown in Figure 2, a kind of portrait dynamic contrast system, comprises each site video signal acquisition device 1, and described video signal acquisition device 1 is connected with streaming media server 2, and what video signal acquisition device 1 was real-time upgrades vision signal to streaming media server 2.In the present embodiment, video signal acquisition device 1 adopts camera, is arranged on the sites such as light rail transit), square, public place of entertainment, Internet bar, community, supermarket and deploys to ensure effective monitoring and control of illegal activities region.In addition in order to cost-saving, the described video acquisition device in present embodiment is divided into channel-style camera head and panorama camera device according to the difference of different position and angle, adopts full-view camera in the nondirectional place of the flow of personnel such as square or community; In supermarket, the place of upper and lower staircase or other staff's uniflux adopts channel-style camera.
Described streaming media server 2 respectively portrait comparison server 3 real-time with video is connected with database update server 5, described video real-time portrait comparison server 3, database update server 5 are all connected with database 4, and described video real-time portrait comparison server 3 is connected with application platform 6.The present inventor is as follows as the principle of work of dynamic contrast system: streaming media server 2 can by camera collection to video information compression after be put on server, user can download limit, limit viewing, be convenient to timely the current intelligence of more new video like this.Video real-time portrait contrast server 3 obtains the camera shooting and video for Identification of Images by access stream media server 2, and real-time comparison video carries out graphical analysis, and by comprising face extraction, feature extraction, feature similarity comparison carry out real-time portrait contrast.If video real-time portrait contrast server 3 carry out real-time portrait contrast after similarity meet the demands; by data base querying personal information, then by related personnel's information transmission to user platform.In addition, database update server 5 also obtains log information or dependent event information by access stream media server 2, then screening is gathered to these information, obtain the video information needing to store, and then the relevant figure information of acquisition is stored in database, make database update, to carry out portrait dynamic contrast in the future.
The invention still further relates to portrait dynamic contrast method, comprise the following steps, as shown in Figure 1a,
Step S101, is arranged on the video information that the channel-style camera of each site and full-view camera gather each net, for carrying out portrait dynamic contrast by native system.
Step S102, form streaming media video file after the portrait video compress collected each site by streaming media server and store, files in stream media contributes to making user can watch video in time.Streaming media video file is used for the access of video real-time portrait comparison server on the one hand, thus carries out real-time portrait comparison.Be used on the other hand the access of database update server, for the figure information in more new database, thus portrait dynamic comparison after being convenient to.
Wherein, carry out real-time portrait comparison and realized by step S103, specific as follows: video real-time portrait comparison server, by access stream media server, obtains the camera video of Identification of Images, carries out graphical analysis, carry out real-time comparison with portrait in database.As shown in Figure 1 b, present embodiment step S103 is further comprising the steps of:
Step S1031, video acquisition, video real-time portrait comparison server, by access stream media server, obtains the camera video for Identification of Images;
Step S1032, face extraction, obtains corresponding facial image from the camera video that step S1031 obtains;
Step S1033, feature extraction, obtains the face characteristic of corresponding site from the facial image obtained;
Step S1034, similarity comparison, carries out similarity comparison by facial image feature in above-mentioned face characteristic and database.
After the comparison of portrait dynamic realtime completes, enter step S104, judge whether similarity meets, if similarity meets, enter step S105; If similarity does not meet, enter step S106;
Step S105, personal information inquiry in database;
Step S106, terminates.
On the other hand, database figure information is upgraded and is realized by following steps,
Step S201, video information stores, the video data information of files in stream media is stored in video information storage unit, and zone bit setting is carried out to video information storage unit, then the scratchpad area (SPA) of database update server is stored in, described sign position setting comprises unique sign index of the transmit leg of portrait video, and all transmit legs are all with unique sign index that the respective take over party as portrait video is general within the scope of data delivery area, such transmit leg just exports the instruction of claimant as video by unique sign index convection media server of the transmit leg with portrait video obtained, described claimant includes the unique sign index with the transmit leg of portrait video as the instruction of video.
Step S202, information sifting weighting, by being added with the video information storage unit of zone bit according to significance level weighting, then screens summation of weighted bits numerical value.
Video information storage unit 7 as shown in Figure 3 a, is divided into data bit 701, summation of weighted bits 702 and zone bit 703, wherein video information is stored in data bit 701 by above step S201 and step S202.Zone bit 703 is used for arranging the position of video information storage unit 7 scratchpad area (SPA) in database update server, can arrange the numerical value of zone bit 703 here in order, like this can so that find the video information in relevant video information storage unit.Summation of weighted bits 702 is used to the video information of being convenient to screen video information storage unit.The video information collected by video signal acquisition device every day due to each site is more, all can not retain storage; Cheese, event are few, like this by being weighted mark to the summation of weighted bits 702 of unit of video information, determine the significance level of associated video information, then delete the video information in the less video information storage unit of weighted value by screening, retain the information in the large video information storage unit of weighted value in addition.
Step S203, figure information obtains, and carries out face extraction and feature extraction, obtain figure information to the video data information screened in the large video information storage unit of the weighted value that stays.
Step S204, figure information stores, and the figure information of acquisition is put into figure information storage unit by database update server.
Step S205, database figure information upgrades, and figure information storage unit in database update server is arranged new zone bit, then the figure information storage unit being added with zone bit is updated in database.
As shown in Figure 3 b, wherein figure information storage unit 401 comprises data bit 402 and zone bit 403 to above step S204 and step S205, and data bit 402 is used for depositing relevant figure information here; Zone bit 403 is also for the ease of searching the position of figure information storage unit 401 in database 4, but zone bit 403 is not simple sequence here, determine after the qualitative classification according to figure information in portrait storage unit 401, here figure information can be assigned to according to the various features such as age, sex character, so that the real-time portrait comparison server 3 of frequency searches the figure information in database, speed and the analytical effect of portrait dynamic contrast can be improved like this.In addition, by figure information storage unit 401 stored in database in after need to add the information relevant to wherein portrait, as identity, educational background, resume etc.
Although the foregoing describe the specific embodiment of the present invention; but those skilled in the art are to be understood that; these only illustrate; various changes or modifications can be made to present embodiment; and not deviating from principle of the present invention and essence, protection scope of the present invention is only defined by the appended claims.
Claims (6)
1. a portrait dynamic contrast method, is characterized in that, comprises the following steps,
Step S101: the portrait video being gathered each site by video acquisition device;
Step S102: form streaming media video file after the portrait video compress collected each site by streaming media server and store;
Step S103: video real-time portrait comparison server, by access stream media server, obtains the camera video of Identification of Images, carries out graphical analysis, carry out real-time comparison with portrait in database;
Step S104: judge whether similarity meets, if similarity meets, enters step S105; If similarity does not meet, enter step S106;
Step S105: personal information inquiry in database;
Step S106: terminate.
2., according to portrait dynamic comparison method according to claim 1, it is characterized in that, described step S103 is further comprising the steps of:
Step S1031: video acquisition, video real-time portrait comparison server, by access stream media server, obtains the camera video for Identification of Images;
Step S1032: face extraction, obtains corresponding facial image from the camera video that step S1031 obtains;
Step S1033: feature extraction, obtains the face characteristic of corresponding site from the facial image obtained;
Step S1034: similarity comparison, carries out similarity comparison by facial image feature in above-mentioned face characteristic and database.
3. according to portrait dynamic contrast method according to claim 1, it is characterized in that, in described step S102, files in stream media also upgrades for database figure information, comprises the following steps:
Step S201: video information stores, the video data information of files in stream media is stored in video information storage unit, and zone bit setting is carried out to video information storage unit, then the scratchpad area (SPA) of database update server is stored in, described sign position setting comprises unique sign index of the transmit leg of portrait video, and all transmit legs are all with unique sign index that the respective take over party as portrait video is general within the scope of data delivery area, such transmit leg just exports the instruction of claimant as video by unique sign index convection media server of the transmit leg with portrait video obtained, described claimant includes the unique sign index with the transmit leg of portrait video as the instruction of video, ,
Step S202: information sifting weighting, by being added with the video information storage unit of zone bit according to significance level weighting, then screens summation of weighted bits numerical value;
Step S203: figure information obtains, the video data information in the video information storage unit stay screening carries out face extraction and feature extraction, obtains figure information;
Step S204: figure information stores, and the figure information of acquisition is put into figure information storage unit by database update server;
Step S205: database figure information upgrades, and figure information storage unit in database update server is arranged new zone bit, then the figure information storage unit being added with zone bit is updated in database.
4. according to portrait dynamic contrast method according to claim 3, it is characterized in that, the zone bit of described step S205 figure information storage unit sets according to the qualitative classification of figure information.
5. a portrait dynamic contrast system, it is characterized in that: comprise each site video signal acquisition device, described video signal acquisition device is connected with streaming media server, described streaming media server respectively portrait comparison server real-time with video is connected with database update server, described video real-time portrait comparison server, database update server are all connected with database, and described video real-time portrait comparison server is connected with application platform.
6. according to portrait dynamic contrast system according to claim 5, it is characterized in that: described video acquisition device is divided into channel-style camera head and panorama camera device according to the difference of different position and angle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410763088.2A CN104484651B (en) | 2014-12-12 | 2014-12-12 | Portrait dynamic contrast method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410763088.2A CN104484651B (en) | 2014-12-12 | 2014-12-12 | Portrait dynamic contrast method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104484651A true CN104484651A (en) | 2015-04-01 |
| CN104484651B CN104484651B (en) | 2017-08-04 |
Family
ID=52759192
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410763088.2A Active CN104484651B (en) | 2014-12-12 | 2014-12-12 | Portrait dynamic contrast method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104484651B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105868719A (en) * | 2016-03-31 | 2016-08-17 | 中山艾华企业管理咨询有限公司 | Face recognition and trace guiding system |
| CN106407953A (en) * | 2016-10-14 | 2017-02-15 | 蔡璟 | Intelligent people searching system based on multi-image big data identification |
| CN106776838A (en) * | 2016-11-24 | 2017-05-31 | 深圳明创自控技术有限公司 | A kind of massive video analysis and quick retrieval system based on cloud computing |
| CN110825891A (en) * | 2019-10-31 | 2020-02-21 | 北京小米移动软件有限公司 | Multimedia information identification method and device and storage medium |
| CN111594271A (en) * | 2020-06-02 | 2020-08-28 | 脑谷人工智能研究院(南京)有限公司 | Coal mine safety monitoring system based on portrait acquisition and processing |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101324919A (en) * | 2007-06-15 | 2008-12-17 | 上海银晨智能识别科技有限公司 | Photograph video contrast method |
| CN102510478A (en) * | 2011-10-28 | 2012-06-20 | 唐玉勇 | Intelligent distribution control system and method used for 'Safe City' project |
| CN102682283A (en) * | 2012-04-09 | 2012-09-19 | 重庆市行安电子科技有限公司 | Dynamic face recognition system |
| US20130216107A1 (en) * | 2012-02-20 | 2013-08-22 | Chih-Hsung Huang | Method of surveillance by face recognition |
-
2014
- 2014-12-12 CN CN201410763088.2A patent/CN104484651B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101324919A (en) * | 2007-06-15 | 2008-12-17 | 上海银晨智能识别科技有限公司 | Photograph video contrast method |
| CN102510478A (en) * | 2011-10-28 | 2012-06-20 | 唐玉勇 | Intelligent distribution control system and method used for 'Safe City' project |
| US20130216107A1 (en) * | 2012-02-20 | 2013-08-22 | Chih-Hsung Huang | Method of surveillance by face recognition |
| CN102682283A (en) * | 2012-04-09 | 2012-09-19 | 重庆市行安电子科技有限公司 | Dynamic face recognition system |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105868719A (en) * | 2016-03-31 | 2016-08-17 | 中山艾华企业管理咨询有限公司 | Face recognition and trace guiding system |
| CN106407953A (en) * | 2016-10-14 | 2017-02-15 | 蔡璟 | Intelligent people searching system based on multi-image big data identification |
| CN106776838A (en) * | 2016-11-24 | 2017-05-31 | 深圳明创自控技术有限公司 | A kind of massive video analysis and quick retrieval system based on cloud computing |
| CN110825891A (en) * | 2019-10-31 | 2020-02-21 | 北京小米移动软件有限公司 | Multimedia information identification method and device and storage medium |
| CN110825891B (en) * | 2019-10-31 | 2023-11-14 | 北京小米移动软件有限公司 | Method and device for identifying multimedia information and storage medium |
| CN111594271A (en) * | 2020-06-02 | 2020-08-28 | 脑谷人工智能研究院(南京)有限公司 | Coal mine safety monitoring system based on portrait acquisition and processing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104484651B (en) | 2017-08-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109117714B (en) | Method, device and system for identifying fellow persons and computer storage medium | |
| CN106339428B (en) | Suspect's personal identification method and device based on video big data | |
| US20130243249A1 (en) | Electronic device and method for recognizing image and searching for concerning information | |
| CN104484651A (en) | Dynamic portrait comparing method and system | |
| CN105450987A (en) | Intelligent recognition platform video monitoring early warning system | |
| CN105205155A (en) | Big data criminal accomplice screening system and method | |
| CN102110122A (en) | Method and device for establishing sample picture index table, method and device for filtering pictures and method and device for searching pictures | |
| CN110750670B (en) | Stranger monitoring method, device and system and storage medium | |
| JP2022518459A (en) | Information processing methods and devices, storage media | |
| KR101354721B1 (en) | Search system and method of search service | |
| CN109492604A (en) | Faceform's characteristic statistics analysis system | |
| CN104866831B (en) | The face recognition algorithms of characteristic weighing | |
| CN108875476B (en) | Automatic near-infrared face registration and recognition method, device and system and storage medium | |
| CN111866196B (en) | Domain name traffic characteristic extraction method, device and equipment and readable storage medium | |
| CN105518644A (en) | Method for processing and displaying real-time social data on map | |
| CN110177255B (en) | Case scheduling-based video information publishing method and system | |
| CN105279496A (en) | Human face recognition method and apparatus | |
| CN106603999A (en) | Video monitoring alarming method and system | |
| CN115103157A (en) | Video analysis method and device based on edge cloud cooperation, electronic equipment and medium | |
| CN113239792A (en) | Big data analysis processing system and method | |
| CN108319672A (en) | Mobile terminal malicious information filtering method and system based on cloud computing | |
| CN104834739A (en) | Internet information storage system | |
| CN106713859A (en) | Image visual monitoring search system and search method thereof | |
| CN117216308B (en) | Searching method, system, equipment and medium based on large model | |
| CN106714007A (en) | Video abstract method and apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: Room 701, 6th Floor, Hengrun Building, No.201 Zhuqiao Road, Suzhou City, Jiangsu Province, 215000 Patentee after: Suzhou Jinnaodai Intelligent System Engineering Co.,Ltd. Address before: Room 510, Ruiji Building, No. 879 Ganjiang Road, Suzhou City, Jiangsu Province, 215000 Patentee before: SUZHOU GOLDEN BRAIN INTELLIGENT SYSTEM ENGINEERING CO.,LTD. |
|
| CP03 | Change of name, title or address |