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CN108304066A - Security identifier visual communication effect quantization method - Google Patents

Security identifier visual communication effect quantization method Download PDF

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Publication number
CN108304066A
CN108304066A CN201810068695.5A CN201810068695A CN108304066A CN 108304066 A CN108304066 A CN 108304066A CN 201810068695 A CN201810068695 A CN 201810068695A CN 108304066 A CN108304066 A CN 108304066A
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China
Prior art keywords
security identifier
observer
visual communication
communication effect
opposite
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Pending
Application number
CN201810068695.5A
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Chinese (zh)
Inventor
陈述
梁霄
蒙锦涛
朱炜
申浩播
郑霞忠
晋良海
汪飞
郭雅薇
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China Three Gorges University CTGU
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China Three Gorges University CTGU
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Priority to CN201810068695.5A priority Critical patent/CN108304066A/en
Publication of CN108304066A publication Critical patent/CN108304066A/en
Pending legal-status Critical Current

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/013Eye tracking input arrangements
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18Eye characteristics, e.g. of the iris
    • G06V40/19Sensors therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18Eye characteristics, e.g. of the iris
    • G06V40/197Matching; Classification

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Multimedia (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Ophthalmology & Optometry (AREA)
  • General Engineering & Computer Science (AREA)
  • Collating Specific Patterns (AREA)

Abstract

The invention discloses a kind of methods of security identifier visual communication effect quantization, this method collects the eye movements indexs such as access time, fixation times, the blinkpunkt of subject personal observations' security identifier by eye tracker, and combines back and find out security identifier visual communication effect quantization method depending on degree matrix.Present invention can apply to evaluate the visual communication effect of security identifier, the conspicuousness of security identifier is judged, reduce the probability that safety accident occurs.

Description

Security identifier visual communication effect quantization method
Technical field
The present invention relates to based on eye movement security identifier visual communication effect quantization method, be specifically used for judging security identifier Visual communication effect it is whether notable.
Background technology
Security identifier is ubiquitous in our life, and security identifier is the important guarantee for avoiding peril.It is not All security identifier all have significant warning function, and quantization safety post is not involved in the relevant criterion of security identifier Know the practicable solution of visual communication effect.
According to《Security identifier and its use directive/guide》(GB2894-2008) etc. relevant criterions, wherein clear stipulaties are various Under situation, the type of security identifier, color, size, material, the requirement that height is set.But it does not illustrate and how to judge The conspicuousness of the visual communication effect of security identifier.
Domestic safety accident emerges one after another at present, wherein having can much be kept away by the warning function of security identifier The generation for exempting from accident, the warning or suggesting effect due to some security identifier are not apparent enough, result in the generation of tragedy.The present invention Exactly it is used for quantifying the visual communication effect of security identifier, the visual communication effect of security identifier is evaluated according to the result obtained Whether significantly, better warning function is provided for people.
Invention content
It is an object of the invention to quantify the visual communication effect of security identifier, the conspicuousness to evaluate security identifier provides A kind of method.
In order to realize above-mentioned technical characteristic, the object of the present invention is achieved like this:Security identifier visual communication effect Quantization method, it is characterised in that include the following steps:
Step 1:The eye movement behavioral data of subject observer is collected using eye tracker;
Step 2:Screen eye movement behavioral data;
Step 3:Collect the eye movement behavioral indicator of relative access time T, opposite fixation times K and opposite pupil diameter E;
Step 4:Eye movement behavioral indicator is determined using analytic hierarchy process (AHP):Relative access time, opposite fixation times and opposite Pupil diameter, the weight of each single item;
Step 5:Determine security identifier visual communication effect quantitative expression formula.
The step 1 detailed process is as follows:The eye movement row of subject observer is collected using Tobii Glass eye trackers For data, including security identifier area, fixation time, blinkpunkt, fixation times, pupil of left eye diameter, pupil of right eye diameter and Eye movement incident duration.
The step 2 detailed process is as follows:Benchmark value-based algorithm is identified according to the eye movement speed of Tobii Glass eye trackers, It is more than 50ms to retain movement speed changing value in the security identifier region of tester's observation to be less than 35 °/s and continue fixation time Blinkpunkt, reject continue fixation time be less than 50ms blinkpunkt, and using Tobii Glass eye trackers handle eye movement behavior The blinkpunkt to match with observer's pupil information in data.
The detailed process of relative access time is as follows in the step 3:
Relative access time of the observer to security identifier region a:
Wherein, t is observer to security identifier region a access times, SaFor the area of security identifier viewing area a, T' is the sum of the unit area access time of Experimental Area;
Wherein, n is experiment overall area number;
Opposite fixation times of the observer to security identifier region a:
Wherein, k is observer to the fixation times of security identifier region a, SaFor the area of security identifier region a, k' For the sum of the unit area fixation times of Experimental Area:
Opposite pupil diameter of the observer to security identifier region a:
Wherein, e is average pupil sizes of the observer to security identifier region a, and e' is observer to Experimental Area Total average pupil sizes.
Weight calculation detailed process in the step 4 is as follows:
The relative access time for the security identifier that experiment is collected, opposite fixation times, opposite pupil diameter constitute n × 3 Matrix:
Following processing is done to matrix A again:
The first step:Matrix A is standardized;
Second step:Every a line normalized of matrix A is obtained into matrix B;
Third walks:The average value for seeking each row of matrix B, obtains one 1 × 3 Matrix C;
4th step:Three indexs of Matrix C are exactly three index weights C=(0.5102 0.3499 0.1399).
Security identifier visual communication effect quantitative expression formula in the step 5:
F=0.5102 × T+0.3499 × K+0.1399 × E (7)
Wherein, T is relative access time, and K is opposite fixation times, and E is opposite pupil diameter.
The method have the advantages that:
1) the present invention provides a kind of methods for weighing security identifier visual communication effect, and related neck is evaluated in security identifier Domain is had no precedent, and has certain theoretical foundation and science.It is potential that some can be solved by this method Security risk greatly reduces the probability that safety accident occurs.
2) eye tracker that the present invention uses is the tool of included data collection and processing, easy to carry, easy to operate, with The rapid development of eye movement technique, eye tracker can be also to have universal feasibility in this way slowly towards whole market.
Specific implementation mode
Embodiments of the present invention are described further below.
Using a kind of security identifier as observation object, the experimental procedure of specific experiment is as follows for this experiment:
Step 1:By acquiring the eye movement data of 5 observers, the eye movement data of record has security identifier area, total The data such as access time, blinkpunkt, fixation times, left pupil diameter, right pupil diameter and duration.Data explanation such as table 1 It is shown:
Table 1:Data explanation
Step 2:Eye movement behavioral data is handled, identifies that a reference value is calculated according to the eye movement speed of Tobii Glass eye trackers Movement speed changing value in the security identifier region of tester's observation is less than 35 °/s and lasting fixation time is more than by method The blinkpunkt of 50ms remains, and the blinkpunkt by lasting fixation time less than 50ms is rejected, and utilizes Tobii Glass eye movements The blinkpunkt to match with observer's pupil information in instrument processing eye movement behavioral data, finally obtains the eye movement behavior after processing Data;
Step 3:Relative access time of the observer to security identifier region a:
Wherein, t is observer to security identifier region a access times, SaFor the area of security identifier viewing area a, T' is the sum of the unit area access time of Experimental Area;
Wherein, n is experiment overall area number;
Opposite fixation times of the observer to security identifier region a:
Wherein, k is observer to the fixation times of security identifier region a, SaFor the area of security identifier region a, k' For the sum of the unit area fixation times of Experimental Area:
Opposite pupil diameter of the observer to security identifier region a:
Wherein, e is average pupil sizes of the observer to security identifier region a, and e' is observer to Experimental Area Total average pupil sizes.
It is handled by the eye movement data of 5 observers to participating in experiment, obtains the eye of each security identifier Dynamic behavioral indicator, as shown in table 2:
The eye movement behavioral indicator numerical value of the every observer of table 2
Person number Relative access time Opposite fixation times Opposite pupil diameter
P1 2.52 2.59 25.61
P2 2.26 2.50 27.09
P3 2.60 2.24 26.01
P4 1.98 1.99 25.79
P5 2.22 2.17 25.67
Step 4:Eye movement behavioral indicator is determined using analytic hierarchy process (AHP):It is relative access time, opposite fixation times, opposite Pupil diameter, the weight of each single item;
By all relative access times of the security identifier of experiment, opposite fixation times, opposite pupil diameter and opposite time 5 × 3 matrix is constituted depending on number:
The first step is standardized matrix A;
Calculating is standardized to matrix using matlab softwares, program thereby is as follows:
Clc;
Clear;
X=[2.52 2.59 25.61 0.5
2.26 2.5 27.09 0.5
2.6 2.24 26.01 0.5
1.98 1.99 25.79 0.5
2.22 2.17 25.67 0.5];
Y=zscore (X);
It is as follows to obtain matrix:
Every a line normalized of matrix A is obtained matrix B by second step;
First, the sum per a line is calculated:
Then, result of calculation is normalized:
4th step seeks the average value of each row of matrix B, obtains one 1 × 3 Matrix C;
Index weights C=(0.5102 0.3499 0.1399);
5th step, the expression formula for obtaining security identifier visual communication effect quantization method are:
Wherein, T is relative access time to F=0.5102 × T+0.3499 × K+0.1399 × E, and K is secondary to watch attentively relatively Number, E are opposite pupil diameter.
By observing expression formula F, it is known that in the entire experiment process, access time of the observer to security identifier Principal element is accounted for, is the main reason for highlighting security identifier visual communication effect, weight accounting has reached 0.5102, next It is opposite fixation times, weight has reached 0.3499, and account for weight proportion minimum is opposite pupil diameter, and weight is 0.1399。
Above-described embodiment is used for illustrating the present invention, rather than limits the invention, the present invention spirit and In scope of the claims, to any modifications and changes that the present invention makes, protection scope of the present invention is both fallen within.

Claims (6)

1. security identifier visual communication effect quantization method, it is characterised in that include the following steps:
Step 1:The eye movement behavioral data of subject observer is collected using eye tracker;
Step 2:Screen eye movement behavioral data;
Step 3:Collect the eye movement behavioral indicator of relative access time T, opposite fixation times K and opposite pupil diameter E;
Step 4:Eye movement behavioral indicator is determined using analytic hierarchy process (AHP):Relative access time, opposite fixation times and opposite pupil Diameter, the weight of each single item;
Step 5:Determine security identifier visual communication effect quantitative expression formula.
2. security identifier visual communication effect quantization method according to claim 1, it is characterised in that:The step 1 tool Body process is as follows:The eye movement behavioral data of subject observer, including security identifier face are collected using Tobii Glass eye trackers Product, fixation time, blinkpunkt, fixation times, pupil of left eye diameter, pupil of right eye diameter and eye movement incident duration.
3. security identifier visual communication effect quantization method according to claim 1, it is characterised in that:The step 2 tool Body process is as follows:Benchmark value-based algorithm is identified according to the eye movement speed of Tobii Glass eye trackers, retains the peace of tester's observation Movement speed changing value less than 35 °/s and continues the blinkpunkt that fixation time is more than 50ms in full identified areas, rejects lasting note It is less than the blinkpunkt of 50ms between apparent time, and believes with observer's pupil using in TobiiGlass eye trackers processing eye movement behavioral data The matched blinkpunkt of manner of breathing.
4. security identifier visual communication effect quantization method according to claim 1, it is characterised in that:In the step 3 The detailed process of relative access time is as follows:
Relative access time of the observer to security identifier region a:
Wherein, t is observer to security identifier region a access times, SaFor the area of security identifier viewing area a, t' is real Test the sum of the unit area access time in region;
Wherein, n is experiment overall area number;
Opposite fixation times of the observer to security identifier region a:
Wherein, k is observer to the fixation times of security identifier region a, SaFor the area of security identifier region a, k' is experiment The sum of the unit area fixation times in region:
Opposite pupil diameter of the observer to security identifier region a:
Wherein, e is average pupil sizes of the observer to security identifier region a, and e' is observer to the total of Experimental Area Average pupil sizes.
5. security identifier visual communication effect quantization method according to claim 1, it is characterised in that:In the step 4 Weight calculation detailed process it is as follows:
The relative access time for the security identifier that experiment is collected, opposite fixation times, opposite pupil diameter constitute the square of n × 3 Battle array:
Following processing is done to matrix A again:
The first step:Matrix A is standardized;
Second step:Every a line normalized of matrix A is obtained into matrix B;
Third walks:The average value for seeking each row of matrix B, obtains one 1 × 3 Matrix C;
4th step:Three indexs of Matrix C are exactly three index weights C=(0.51020.34990.1399).
6. security identifier visual communication effect quantization method according to claim 1, it is characterised in that:In the step 5 Security identifier visual communication effect quantitative expression formula:
F=0.5102 × T+0.3499 × K+0.1399 × E (7)
Wherein, T is relative access time, and K is opposite fixation times, and E is opposite pupil diameter.
CN201810068695.5A 2018-01-24 2018-01-24 Security identifier visual communication effect quantization method Pending CN108304066A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109948687A (en) * 2019-03-13 2019-06-28 上海工程技术大学 Security identifier visual communication effect quantization method
CN113208611A (en) * 2021-04-13 2021-08-06 中南民族大学 Fatigue driving real-time monitoring system integrating machine learning and Internet of things technology

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CN105438066A (en) * 2014-08-22 2016-03-30 怡利电子工业股份有限公司 Device for simultaneously displaying navigation information and traffic safety prompting information
WO2016051136A1 (en) * 2014-09-30 2016-04-07 Ibisvision Limited Method, software and apparatus for testing a patient's visual field
CN105608834A (en) * 2014-09-30 2016-05-25 波音公司 Event detection system
CN105844257A (en) * 2016-04-11 2016-08-10 吉林大学 Early warning system based on machine vision driving-in-fog road denoter missing and early warning method
CN106169063A (en) * 2016-06-22 2016-11-30 江苏大学 A kind of method in automatic identification user's reading interest district
CN106973266A (en) * 2017-03-31 2017-07-21 三峡大学 Substation safety operation management and control system and method
CN107180310A (en) * 2017-06-01 2017-09-19 三峡大学 A kind of method for automatically determining job site safety sign board layout area

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105438066A (en) * 2014-08-22 2016-03-30 怡利电子工业股份有限公司 Device for simultaneously displaying navigation information and traffic safety prompting information
WO2016051136A1 (en) * 2014-09-30 2016-04-07 Ibisvision Limited Method, software and apparatus for testing a patient's visual field
CN105608834A (en) * 2014-09-30 2016-05-25 波音公司 Event detection system
CN105844257A (en) * 2016-04-11 2016-08-10 吉林大学 Early warning system based on machine vision driving-in-fog road denoter missing and early warning method
CN106169063A (en) * 2016-06-22 2016-11-30 江苏大学 A kind of method in automatic identification user's reading interest district
CN106973266A (en) * 2017-03-31 2017-07-21 三峡大学 Substation safety operation management and control system and method
CN107180310A (en) * 2017-06-01 2017-09-19 三峡大学 A kind of method for automatically determining job site safety sign board layout area

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109948687A (en) * 2019-03-13 2019-06-28 上海工程技术大学 Security identifier visual communication effect quantization method
CN113208611A (en) * 2021-04-13 2021-08-06 中南民族大学 Fatigue driving real-time monitoring system integrating machine learning and Internet of things technology

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