CN102073857A - Multimodal driver fatigue detection method and special equipment thereof - Google Patents
Multimodal driver fatigue detection method and special equipment thereof Download PDFInfo
- Publication number
- CN102073857A CN102073857A CN2011100243902A CN201110024390A CN102073857A CN 102073857 A CN102073857 A CN 102073857A CN 2011100243902 A CN2011100243902 A CN 2011100243902A CN 201110024390 A CN201110024390 A CN 201110024390A CN 102073857 A CN102073857 A CN 102073857A
- Authority
- CN
- China
- Prior art keywords
- fatigue
- driver
- head
- judge
- detection method
- 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.)
- Pending
Links
Images
Landscapes
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention provides a multimodal driver fatigue detection method and special equipment thereof. The special equipment comprises a dual-channel vision detection device, a multipoint pressure detection device and a physiological signal real-time detection device which are used for detecting the motion trails of heads, forms of human eyes and mouths, multipoint pressure change curves and pulses, so that information is subjected to multimodal fusion to form a set of multi-characteristic fatigue evaluation scheme; and the accuracy of fatigue detection is increased by multiple fatigue characteristics under the condition that the normal operation of drivers is not interfered. The system design gives priority to practicability, operability and humanization, and the stability and safety and reliability of the system is ensured. The method is reasonable, simple in device, accurate in detection and high in operability, and is favorable for popularization and application.
Description
Technical field
The present invention relates to method and specialized equipment thereof that a kind of driver fatigue detects, relate in particular to a kind of multi-modal driver fatigue detection method
And specialized equipment.
Background technology
Fatigue driving is a key factor that causes traffic hazard, if can detect automatically driver fatigue state, and in time reports to the police, and will effectively reduce the generation of traffic hazard.Existing fatigue detecting method has detection and problems such as evaluation means is single, actual working environment complexity, is difficult to satisfy the practical application needs.And train and long-distance transport automobile be as the important vehicles, and freight volume is big, driver's working time is long, easily sleepy, causes traffic hazard easily, and at present domestic still do not have practical driver fatigue detection and a warning device.
Summary of the invention
Goal of the invention: the invention provides a kind of multi-modal driver fatigue detection method
And specialized equipment, its objective is detection that exists in the solution detection method in the past and problems such as evaluation means is single, actual working environment complexity.
Technical scheme: the present invention is achieved through the following technical solutions:
Multi-modal driver fatigue detection method
, it is characterized in that: the concrete steps of described method are as follows:
The first step: binary channels image acquisition;
⑴, passage one are the wide-angle imaging head, this camera position and direction are fixed, the wide-angle imaging head is gathered complete image in the pilothouse, set up 3 d space coordinate system, in the image that collects in conjunction with the background priori, carry out people's face and detect, judge the three-dimensional coordinate information of driver's head in the space;
⑵, passage two are high-resolution camera, and its position and angle can three-dimensionally move, and the head coordinate information that obtains according to passage 1 passes to passage two, and the shooting angle of placed channel two cameras is obtained driver's face image thus;
Second step: head position three-dimensional coordinate and movement locus are determined
⑴ the image that, the wide-angle imaging head of fixing by position and direction in the passage one provide according to the people face part in priori and the people's face colouring information positioning image, is determined the coordinate information of people's face in three dimensions;
, again by people face part and coordinate information thereof in the fixing wide-angle imaging head abstraction sequence image of position in the passage one and direction, obtain the track of sequence coordinate in three dimensions; Movement locus according to head determines whether to be fatigue state;
The 3rd step: eyes closed state-detection
In conjunction with template matches and integral projection method, on the image that the high-resolution camera that three-dimensional moves is gathered, determine position of human eye; Judge the eyes stretching degree at position of human eye then,, then be judged as closure if less than certain exposed area; Closed degree according to human eye judges whether fatigue;
The 4th step: the mouth open configuration detects
⑴ mouth position is estimated in the position of the human eye that, the high-resolution camera that moves according to three-dimensional are gathered, and seeks the mouth edge unique point near this position;
⑵, analyze the distribution of mouth unique point,, then be judged as the action of magnifying if unique point is divided too far awayly up and down; Action judges whether fatigue according to face;
The 5th step: multiple spot pressure detection and fatigue state detect
, respectively at four jiaos of seats and two jiaos of placement force sensors of backrest of driver, read this force value of 6 in real time;
⑵, the force value of obtaining is carried out filtering operation, remove vehicle advance in the pressure surge that causes of vibration; On pressure curve, seek singular value, judge whether to be fatigue state;
The 6th step: wireless pulse real-time detection apparatus
Gather pulse signal and driver's normal pulse frequency ratio by pulse transducer, judge whether to be fatigue state;
Judge whether to the method for fatigue state in second step to be: according to the head 3 D motion trace, if judge driver's head in 1 second downward fast moving is arranged, perhaps the angle of head and health exceeds allowed band, then can be judged as fatigue state.
Judge whether to the method for fatigue state in the 3rd step to be: the sequence object is carried out the human eye closure state judge, if closure state then was judged as fatigue state greater than 0.5 second continuously.
Judge whether to the method for fatigue state in the 4th step to be: the sequence object is carried out the mouth open configuration judge,, then be judged as fatigue state if magnify state continuously greater than 3 seconds.
Judge whether to the method for fatigue state in the 5th step to be: on pressure curve, seek singular value, be flat condition, then be judged as fatigue state if having 3 or above pressure curve to surpass 100 seconds.
Judge whether to the method for fatigue state in the 6th step to be:, judge tired when detecting pulse when slack-off.
Fatigue detecting characteristic synthetic analysis with second to six step obtained obtains the weights of various fatigue factors according to experimental result, and judges tired situation, then reports to the police in pilothouse if produce tired situation.
Be applied in aforesaid multi-modal driver fatigue detection method
In specialized equipment, it is characterized in that: described equipment comprises binary channels vision inspection apparatus, multiple spot pressure-detecting device, physiological signal real-time detection apparatus, warning device and CPU (central processing unit); Described binary channels vision inspection apparatus, multiple spot pressure-detecting device and physiological signal real-time detection apparatus all are connected to CPU (central processing unit), and CPU (central processing unit) connects warning device.
Described binary channels vision inspection apparatus comprises that wide-angle imaging head that position and direction are fixing and position and angle can the three-dimensional high-resolution cameras that moves; The multiple spot pressure-detecting device is the pressure transducer that is arranged on two jiaos on driver's four jiaos of seats and backrest; The physiological signal real-time detection apparatus is a pulse transducer.
Pulse transducer is the Wrist belt-type structure, and adopts short distance embedded radio communication pattern, and frequency of operation is 300～1000M.
Advantage and effect: the present invention relates to a kind of multi-modal driver fatigue detection method
And specialized equipment
The designed system of this project comprises the binary channels vision inspection apparatus, multiple spot pressure-detecting device and physiological signal real-time detection apparatus, detect head movement locus, human eye and mouth form, multiple spot pressure history and pulse flow respectively, thereby information is carried out multi-modal fusion, form the tired evaluation of programme of the many features of a cover, under the situation of not disturbing driver's operate as normal, utilize a plurality of fatigue characteristics, increase the accuracy of fatigue detecting.Based on practicality, operability, human oriented design, guarantee the stability of system and safe and reliable in this system design.
This inventive method rationally, device is succinct, detection is accurate, workable, is beneficial to and applies.
Description of drawings:
Fig. 1 is the theory diagram of multi-modal driver fatigue detection method of the present invention;
Fig. 2 is a multi-modal driver fatigue detection method of the present invention
In the specialized equipment block diagram.
Embodiment:The present invention is described further below in conjunction with accompanying drawing:
The invention provides a kind of multi-modal driver fatigue detection method
It is characterized in that: the concrete steps of described method are as follows:
The first step: binary channels image acquisition;
⑴, passage one are the wide-angle imaging head, this camera position and direction are fixed, the wide-angle imaging head is gathered complete image in the pilothouse, set up 3 d space coordinate system, in the image that collects in conjunction with the background priori, carry out people's face and detect, judge the three-dimensional coordinate information of driver's head in the space;
⑵, passage two are high-resolution camera, and its position and angle can three-dimensionally move, and the head coordinate information that obtains according to passage 1 passes to passage two, and the shooting angle of placed channel two cameras is obtained driver's face image thus;
Second step: head position three-dimensional coordinate and movement locus are determined
The people is in fatigue, the unconscious action of bowing can take place, can be by sequence image head position in judging 1 second, judge whether to take place this action, if have then be judged as fatigue state, perhaps head and health angle exceed normal operation range, also are judged as fatigue state, and this detection implementation procedure mainly is that the sequence image that passage one collects is carried out analyzing and processing:
⑴ the image that, the wide-angle imaging head of fixing by position and direction in the passage one provide according to the people face part in priori and the people's face colouring information positioning image, is determined the coordinate information of people's face in three dimensions;
, again by people face part and coordinate information thereof in the fixing wide-angle imaging head abstraction sequence image of position and direction, obtain the track of sequence coordinate in three dimensions; Movement locus according to head determines whether to be fatigue state;
Judge whether that the method for fatigue state is according to the head 3 D motion trace, if judge driver's head in 1 second downward fast moving is arranged, perhaps the angle of head and health exceeds allowed band, then can be judged as fatigue state.
The 3rd step: eyes closed state-detection
In conjunction with template matches and integral projection method, on the image that the high-resolution camera that three-dimensional moves is gathered, determine position of human eye; Judge the eyes stretching degree at position of human eye then,, then be judged as closure if less than certain exposed area; Closed degree according to human eye judges whether fatigue; Judge whether to the method for fatigue state to be: the sequence object is carried out the human eye closure state judge, if closure state then was judged as fatigue state greater than 0.5 second continuously.
The 4th step: the mouth open configuration detects
⑴ mouth position is estimated in the position of the human eye that, the high-resolution camera that moves according to three-dimensional are gathered, and seeks the mouth edge unique point near this position;
⑵, analyze the distribution of mouth unique point,, then be judged as the action of magnifying if unique point is divided too far awayly up and down; Action judges whether fatigue according to face;
Judge whether to the method for fatigue state to be: the sequence object is carried out the mouth open configuration judge,, then be judged as fatigue state if magnify state continuously greater than 3 seconds.
The 5th step: design of multiple spot pressure-detecting device and fatigue state detect
, respectively at four jiaos of seats and two jiaos of placement force sensors of backrest of driver, read this force value of 6 in real time;
⑵, the force value of obtaining is carried out filtering operation, remove vehicle advance in the pressure surge that causes of vibration; On pressure curve, seek singular value, judge whether to be fatigue state; Judge whether to the method for fatigue state to be: on pressure curve, seek singular value, be flat condition, then be judged as fatigue state if having 3 or above pressure curve to surpass 100 seconds.
The 6th step: wireless pulse real-time detection apparatus
Gather pulse signal and driver's normal pulse frequency ratio by pulse transducer, judge whether to be fatigue state; Judge whether to the method for fatigue state to be: when detecting pulse when slack-off, judge tiredly, device starts, and reminds the driver to keep clear-headed.The pulse transducer of this device adopts short distance embedded radio communication pattern, and frequency of operation 300～1000M is adjustable, powered battery, and power consumption is little, and radiation is low.Pulse transducer can be made Wrist belt-type, and sizableness is in a wrist-watch, and during use, the driver only need be worn on the wrist and get final product, and is easy to operate, do not influence driver's normal running.
The 7th step:Go on foot the fatigue detecting characteristic synthetic analysis of obtaining with second to six, obtain the weights of various fatigue factors according to experimental result, and judge tired situation, then in pilothouse, report to the police if produce tired situation, warning can be adopted the form of playing back music, reminds the driver to concentrate one's energy to drive.
Method of the present invention is to realize by following device: described device comprises binary channels vision inspection apparatus, multiple spot pressure-detecting device, physiological signal real-time detection apparatus, warning device and CPU (central processing unit); Described binary channels vision inspection apparatus, multiple spot pressure-detecting device and physiological signal real-time detection apparatus all are connected to CPU (central processing unit), CPU (central processing unit) connects warning device, the various signal datas that to gather in CPU (central processing unit) are handled, whether detect is fatigue state, if be fatigue state, then report to the police by warning device.
Described binary channels vision inspection apparatus comprises that wide-angle imaging head that position and direction are fixing and position and angle can the three-dimensional high-resolution cameras that moves, and wide-angle imaging head and high-resolution camera are used to detect head movement locus, human eye and mouth form; The multiple spot pressure-detecting device is the pressure transducer that is arranged on two jiaos on driver's four jiaos of seats and backrest, and pressure transducer is used to detect the multiple spot pressure history; The physiological signal real-time detection apparatus is a pulse transducer, and pulse transducer is used to detect pulse flow.
Pulse transducer is the Wrist belt-type structure, and adopts short distance embedded radio communication pattern, and frequency of operation is 300～1000M.
It is accurate and effective that method and apparatus of the present invention detects effect, not omission, for fatigue driving, have good detection and reminding effect, whether the detection method of the present invention by the comprehensive multi-angle of multipath detects the driver tired, guaranteed accuracy rate fully, be beneficial to and using aspect the detection fatigue driving.
Claims (10)
1. multi-modal driver fatigue detection method
, it is characterized in that: the concrete steps of described method are as follows:
The first step: binary channels image acquisition;
⑴, passage one are the wide-angle imaging head, this camera position and direction are fixed, the wide-angle imaging head is gathered complete image in the pilothouse, set up 3 d space coordinate system, in the image that collects in conjunction with the background priori, carry out people's face and detect, judge the three-dimensional coordinate information of driver's head in the space;
⑵, passage two are high-resolution camera, and its position and angle can three-dimensionally move, and the head coordinate information that obtains according to passage 1 passes to passage two, and the shooting angle of placed channel two cameras is obtained driver's face image thus;
Second step: head position three-dimensional coordinate and movement locus are determined
⑴ the image that, the wide-angle imaging head of fixing by position and direction in the passage one provide according to the people face part in priori and the people's face colouring information positioning image, is determined the coordinate information of people's face in three dimensions;
, again by people face part and coordinate information thereof in the fixing wide-angle imaging head abstraction sequence image of position in the passage one and direction, obtain the track of sequence coordinate in three dimensions; Movement locus according to head determines whether to be fatigue state;
The 3rd step: eyes closed state-detection
In conjunction with template matches and integral projection method, on the image that the high-resolution camera that three-dimensional moves is gathered, determine position of human eye; Judge the eyes stretching degree at position of human eye then,, then be judged as closure if less than certain exposed area; Closed degree according to human eye judges whether fatigue;
The 4th step: the mouth open configuration detects
⑴ mouth position is estimated in the position of the human eye that, the high-resolution camera that moves according to three-dimensional are gathered, and seeks the mouth edge unique point near this position;
⑵, analyze the distribution of mouth unique point,, then be judged as the action of magnifying if unique point is divided too far awayly up and down; Action judges whether fatigue according to face;
The 5th step: multiple spot pressure detection and fatigue state detect
, respectively at four jiaos of seats and two jiaos of placement force sensors of backrest of driver, read this force value of 6 in real time;
⑵, the force value of obtaining is carried out filtering operation, remove vehicle advance in the pressure surge that causes of vibration; On pressure curve, seek singular value, judge whether to be fatigue state;
The 6th step: wireless pulse real-time detection apparatus
Gather pulse signal and driver's normal pulse frequency ratio by pulse transducer, judge whether to be fatigue state.
2. multi-modal driver fatigue detection method according to claim 1
It is characterized in that: judge whether to the method for fatigue state in second step to be: according to the head 3 D motion trace, if judge driver's head in 1 second downward fast moving is arranged, perhaps the angle of head and health exceeds allowed band, then can be judged as fatigue state.
3. multi-modal driver fatigue detection method according to claim 1
, it is characterized in that: judge whether to the method for fatigue state in the 3rd step to be: the sequence object is carried out the human eye closure state judge, if closure state then was judged as fatigue state greater than 0.5 second continuously.
4. multi-modal driver fatigue detection method according to claim 1
, it is characterized in that: judge whether to the method for fatigue state in the 4th step to be: the sequence object is carried out the mouth open configuration judge,, then be judged as fatigue state if magnify state continuously greater than 3 seconds.
5. multi-modal driver fatigue detection method according to claim 1
, it is characterized in that: judge whether to the method for fatigue state in the 5th step to be: on pressure curve, seek singular value, be flat condition, then be judged as fatigue state if having 3 or above pressure curve to surpass 100 seconds.
6. multi-modal driver fatigue detection method according to claim 1
, it is characterized in that: judge whether to the method for fatigue state in the 6th step to be:, judge tired when detecting pulse when slack-off.
7. multi-modal driver fatigue detection method according to claim 1
, it is characterized in that: the fatigue detecting characteristic synthetic analysis with second to six step obtained, obtain the weights of various fatigue factors according to experimental result, and judge tired situation, then in pilothouse, report to the police if produce tired situation.
8. be applied in the described multi-modal driver fatigue detection method of claim 1
In specialized equipment, it is characterized in that: described equipment comprises binary channels vision inspection apparatus, multiple spot pressure-detecting device, physiological signal real-time detection apparatus, warning device and CPU (central processing unit); Described binary channels vision inspection apparatus, multiple spot pressure-detecting device and physiological signal real-time detection apparatus all are connected to CPU (central processing unit), and CPU (central processing unit) connects warning device.
9. multi-modal driver fatigue detection method according to claim 1
In specialized equipment
, it is characterized in that: described binary channels vision inspection apparatus comprises that wide-angle imaging head that position and direction are fixing and position and angle can the three-dimensional high-resolution cameras that moves; The multiple spot pressure-detecting device is the pressure transducer that is arranged on two jiaos on driver's four jiaos of seats and backrest; The physiological signal real-time detection apparatus is a pulse transducer.
10. multi-modal driver fatigue detection method according to claim 9
In specialized equipment
, it is characterized in that: pulse transducer is the Wrist belt-type structure, and adopts short distance embedded radio communication pattern, frequency of operation is 300～1000M.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011100243902A CN102073857A (en) | 2011-01-24 | 2011-01-24 | Multimodal driver fatigue detection method and special equipment thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011100243902A CN102073857A (en) | 2011-01-24 | 2011-01-24 | Multimodal driver fatigue detection method and special equipment thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102073857A true CN102073857A (en) | 2011-05-25 |
Family
ID=44032391
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011100243902A Pending CN102073857A (en) | 2011-01-24 | 2011-01-24 | Multimodal driver fatigue detection method and special equipment thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102073857A (en) |
Cited By (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102881117A (en) * | 2012-06-15 | 2013-01-16 | 浙江吉利汽车研究院有限公司杭州分公司 | Watch capable of detecting fatigue of driver |
| CN102991377A (en) * | 2012-09-25 | 2013-03-27 | 浙江理工大学 | Vehicle cam type vibrating seat |
| CN104616438A (en) * | 2015-03-02 | 2015-05-13 | 重庆市科学技术研究院 | Yawning action detection method for detecting fatigue driving |
| CN104616437A (en) * | 2015-02-27 | 2015-05-13 | 浪潮集团有限公司 | Vehicle-mounted fatigue identification system and method |
| CN105249976A (en) * | 2015-11-26 | 2016-01-20 | 中山大学 | Driver fatigue monitoring method and system based on head monitoring |
| CN105354987A (en) * | 2015-11-26 | 2016-02-24 | 南京工程学院 | Vehicle fatigue driving detection and identity authentication apparatus, and detection method thereof |
| CN105469466A (en) * | 2015-12-04 | 2016-04-06 | 北海创思电子科技产业有限公司 | EDR (event data recorder) with sound recognition function |
| CN105469467A (en) * | 2015-12-04 | 2016-04-06 | 北海创思电子科技产业有限公司 | EDR (event data recorder) capable of monitoring fatigue driving |
| CN105701445A (en) * | 2014-12-15 | 2016-06-22 | 爱信精机株式会社 | determination apparatus and determination method |
| CN105761431A (en) * | 2016-05-05 | 2016-07-13 | 中晟国计科技有限公司 | Behavior monitor early-warning method and system |
| CN105825631A (en) * | 2016-04-26 | 2016-08-03 | 成都远控科技有限公司 | Video intelligent algorithm-based fatigue detection method and system |
| CN105957310A (en) * | 2016-05-24 | 2016-09-21 | 北京小米移动软件有限公司 | Rest prompting method, device and equipment in driving process |
| CN104182995B (en) * | 2014-08-08 | 2017-02-15 | 吉林大学 | Highway roadside landscape color evaluation method based on driving fatigue |
| CN106781284A (en) * | 2016-12-31 | 2017-05-31 | 中国铁道科学研究院电子计算技术研究所 | Trainman's driver fatigue monitor system based on Multi-information acquisition |
| CN106843455A (en) * | 2015-12-03 | 2017-06-13 | 致伸科技股份有限公司 | Tired caution system |
| CN107648719A (en) * | 2017-08-23 | 2018-02-02 | 中国人民解放军总医院 | The eye wearable system stimulated based on fatigue detecting with awakening |
| CN107688884A (en) * | 2016-08-04 | 2018-02-13 | 同方威视技术股份有限公司 | Safety check centralized management system |
| CN108182377A (en) * | 2017-11-21 | 2018-06-19 | 合肥工业大学 | Human eye sight detection method and device based on photogrammetric technology |
| WO2019011124A1 (en) * | 2017-07-12 | 2019-01-17 | Huawei Technologies Co., Ltd. | Integrated system for detection of driver condition |
| CN109508576A (en) * | 2017-09-14 | 2019-03-22 | 杭州海康威视数字技术股份有限公司 | A kind of abnormal driving behavioral value method, apparatus and electronic equipment |
| CN109847168A (en) * | 2019-01-22 | 2019-06-07 | 中国科学院苏州生物医学工程技术研究所 | Wearable fatigue detecting and interfering system |
| CN109985301A (en) * | 2017-12-29 | 2019-07-09 | 新华网股份有限公司 | Reduce the treating method and apparatus of fatigue |
| CN110329267A (en) * | 2018-03-28 | 2019-10-15 | 马自达汽车株式会社 | Driver condition assessment device |
| CN110859609A (en) * | 2019-11-26 | 2020-03-06 | 郑州迈拓信息技术有限公司 | Multi-feature fusion fatigue driving detection method based on voice analysis |
| CN110956068A (en) * | 2019-05-29 | 2020-04-03 | 初速度（苏州）科技有限公司 | Fatigue detection method and device based on human eye state recognition |
| CN111767885A (en) * | 2020-07-07 | 2020-10-13 | 歌尔科技有限公司 | Fatigue state identification method, device, equipment, readable storage medium and system |
| CN112036217A (en) * | 2019-06-04 | 2020-12-04 | 初速度（苏州）科技有限公司 | Person state detection method and device based on mouth information |
| CN112084820A (en) * | 2019-06-14 | 2020-12-15 | 初速度（苏州）科技有限公司 | Personnel state detection method and device based on head information |
| WO2021159269A1 (en) * | 2020-02-11 | 2021-08-19 | 云图技术有限公司 | Vision-based safe driving early warning method and system, and storage medium |
| CN115346340A (en) * | 2022-07-21 | 2022-11-15 | 浙江极氪智能科技有限公司 | Device and method for improving driving fatigue |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101540090A (en) * | 2009-04-14 | 2009-09-23 | 华南理工大学 | Driver fatigue monitoring device based on multivariate information fusion and monitoring method thereof |
| CN101739549A (en) * | 2009-02-11 | 2010-06-16 | 北京智安邦科技有限公司 | Face detection method and system |
| CN101950355A (en) * | 2010-09-08 | 2011-01-19 | 中国人民解放军国防科学技术大学 | Method for detecting fatigue state of driver based on digital video |
-
2011
- 2011-01-24 CN CN2011100243902A patent/CN102073857A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101739549A (en) * | 2009-02-11 | 2010-06-16 | 北京智安邦科技有限公司 | Face detection method and system |
| CN101540090A (en) * | 2009-04-14 | 2009-09-23 | 华南理工大学 | Driver fatigue monitoring device based on multivariate information fusion and monitoring method thereof |
| CN101950355A (en) * | 2010-09-08 | 2011-01-19 | 中国人民解放军国防科学技术大学 | Method for detecting fatigue state of driver based on digital video |
Non-Patent Citations (3)
| Title |
|---|
| 刘振宇等: "多模态疲劳检测方法研究", 《PROCEEDINGS OF 2010 FIRST INTERNATIONAL CONFERENCE ON CELLULAR,MOLECULAR BIOLOGY, BIOPHYSICS AND BIOENGINEERING(VOLUME 4)》 * |
| 刘振宇等: "多模态疲劳检测方法研究", 《PROCEEDINGS OF 2010 FIRST INTERNATIONAL CONFERENCE ON CELLULAR,MOLECULAR BIOLOGY, BIOPHYSICS AND BIOENGINEERING(VOLUME 4)》, 31 December 2010 (2010-12-31) * |
| 朱学峰等: "基于模糊控制的驾驶疲劳检测", 《计算机工程与设计》 * |
Cited By (41)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102881117B (en) * | 2012-06-15 | 2014-11-12 | 浙江吉利汽车研究院有限公司杭州分公司 | Watch capable of detecting fatigue of driver |
| CN102881117A (en) * | 2012-06-15 | 2013-01-16 | 浙江吉利汽车研究院有限公司杭州分公司 | Watch capable of detecting fatigue of driver |
| CN102991377A (en) * | 2012-09-25 | 2013-03-27 | 浙江理工大学 | Vehicle cam type vibrating seat |
| CN102991377B (en) * | 2012-09-25 | 2017-03-29 | 浙江理工大学 | A kind of automobile-used cam-type vibration seat |
| CN104182995B (en) * | 2014-08-08 | 2017-02-15 | 吉林大学 | Highway roadside landscape color evaluation method based on driving fatigue |
| CN105701445A (en) * | 2014-12-15 | 2016-06-22 | 爱信精机株式会社 | determination apparatus and determination method |
| CN104616437A (en) * | 2015-02-27 | 2015-05-13 | 浪潮集团有限公司 | Vehicle-mounted fatigue identification system and method |
| CN104616438A (en) * | 2015-03-02 | 2015-05-13 | 重庆市科学技术研究院 | Yawning action detection method for detecting fatigue driving |
| CN105354987B (en) * | 2015-11-26 | 2018-06-08 | 南京工程学院 | Vehicle-mounted type fatigue driving detection and identification authentication system and its detection method |
| CN105354987A (en) * | 2015-11-26 | 2016-02-24 | 南京工程学院 | Vehicle fatigue driving detection and identity authentication apparatus, and detection method thereof |
| CN105249976A (en) * | 2015-11-26 | 2016-01-20 | 中山大学 | Driver fatigue monitoring method and system based on head monitoring |
| CN106843455A (en) * | 2015-12-03 | 2017-06-13 | 致伸科技股份有限公司 | Tired caution system |
| CN105469467A (en) * | 2015-12-04 | 2016-04-06 | 北海创思电子科技产业有限公司 | EDR (event data recorder) capable of monitoring fatigue driving |
| CN105469466A (en) * | 2015-12-04 | 2016-04-06 | 北海创思电子科技产业有限公司 | EDR (event data recorder) with sound recognition function |
| CN105825631A (en) * | 2016-04-26 | 2016-08-03 | 成都远控科技有限公司 | Video intelligent algorithm-based fatigue detection method and system |
| CN105825631B (en) * | 2016-04-26 | 2018-01-16 | 成都远控科技有限公司 | fatigue detection method and system based on video intelligent algorithm |
| CN105761431A (en) * | 2016-05-05 | 2016-07-13 | 中晟国计科技有限公司 | Behavior monitor early-warning method and system |
| CN105957310A (en) * | 2016-05-24 | 2016-09-21 | 北京小米移动软件有限公司 | Rest prompting method, device and equipment in driving process |
| CN107688884A (en) * | 2016-08-04 | 2018-02-13 | 同方威视技术股份有限公司 | Safety check centralized management system |
| CN106781284A (en) * | 2016-12-31 | 2017-05-31 | 中国铁道科学研究院电子计算技术研究所 | Trainman's driver fatigue monitor system based on Multi-information acquisition |
| US10592785B2 (en) | 2017-07-12 | 2020-03-17 | Futurewei Technologies, Inc. | Integrated system for detection of driver condition |
| WO2019011124A1 (en) * | 2017-07-12 | 2019-01-17 | Huawei Technologies Co., Ltd. | Integrated system for detection of driver condition |
| CN107648719A (en) * | 2017-08-23 | 2018-02-02 | 中国人民解放军总医院 | The eye wearable system stimulated based on fatigue detecting with awakening |
| CN109508576A (en) * | 2017-09-14 | 2019-03-22 | 杭州海康威视数字技术股份有限公司 | A kind of abnormal driving behavioral value method, apparatus and electronic equipment |
| CN108182377A (en) * | 2017-11-21 | 2018-06-19 | 合肥工业大学 | Human eye sight detection method and device based on photogrammetric technology |
| CN109985301A (en) * | 2017-12-29 | 2019-07-09 | 新华网股份有限公司 | Reduce the treating method and apparatus of fatigue |
| CN110329267A (en) * | 2018-03-28 | 2019-10-15 | 马自达汽车株式会社 | Driver condition assessment device |
| CN110329267B (en) * | 2018-03-28 | 2022-08-09 | 马自达汽车株式会社 | Driver state determination device |
| CN109847168A (en) * | 2019-01-22 | 2019-06-07 | 中国科学院苏州生物医学工程技术研究所 | Wearable fatigue detecting and interfering system |
| CN109847168B (en) * | 2019-01-22 | 2022-03-08 | 中国科学院苏州生物医学工程技术研究所 | Wearable fatigue detection and intervention system |
| CN110956068A (en) * | 2019-05-29 | 2020-04-03 | 初速度（苏州）科技有限公司 | Fatigue detection method and device based on human eye state recognition |
| CN110956068B (en) * | 2019-05-29 | 2022-06-10 | 魔门塔(苏州)科技有限公司 | Fatigue detection method and device based on human eye state recognition |
| CN112036217A (en) * | 2019-06-04 | 2020-12-04 | 初速度（苏州）科技有限公司 | Person state detection method and device based on mouth information |
| CN112036217B (en) * | 2019-06-04 | 2022-06-21 | 魔门塔(苏州)科技有限公司 | Person state detection method and device based on mouth information |
| CN112084820A (en) * | 2019-06-14 | 2020-12-15 | 初速度（苏州）科技有限公司 | Personnel state detection method and device based on head information |
| CN112084820B (en) * | 2019-06-14 | 2022-06-24 | 魔门塔(苏州)科技有限公司 | Personnel state detection method and device based on head information |
| CN110859609A (en) * | 2019-11-26 | 2020-03-06 | 郑州迈拓信息技术有限公司 | Multi-feature fusion fatigue driving detection method based on voice analysis |
| WO2021159269A1 (en) * | 2020-02-11 | 2021-08-19 | 云图技术有限公司 | Vision-based safe driving early warning method and system, and storage medium |
| CN111767885A (en) * | 2020-07-07 | 2020-10-13 | 歌尔科技有限公司 | Fatigue state identification method, device, equipment, readable storage medium and system |
| CN115346340A (en) * | 2022-07-21 | 2022-11-15 | 浙江极氪智能科技有限公司 | Device and method for improving driving fatigue |
| CN115346340B (en) * | 2022-07-21 | 2023-11-17 | 浙江极氪智能科技有限公司 | Device and method for improving driving fatigue |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102073857A (en) | Multimodal driver fatigue detection method and special equipment thereof | |
| CN104794855B (en) | Driver attention's comprehensive evaluating device | |
| CN104183091B (en) | System for adjusting sensitivity of fatigue driving early warning system in self-adaptive mode | |
| CN106327801B (en) | Method for detecting fatigue driving and device | |
| CN105574537B (en) | Dangerous driving behavior testing and evaluation method based on multisensor | |
| CN202078318U (en) | Multi-modality fatigue detection equipment for driver | |
| CN103770780B (en) | A kind of active safety systems of vehicles alarm shield device | |
| CN102509418B (en) | Fatigue driving estimation and early-warning method and device of multi-sensor information fusion | |
| CN104112334B (en) | Fatigue driving method for early warning and system | |
| CN103680246B (en) | The drive safety examination evaluation system distributing based on vision attention | |
| CN103767715B (en) | A kind of driver safety driving state detection device | |
| CN102208125B (en) | Fatigue driving monitoring system and method thereof | |
| CN105719431A (en) | Fatigue driving detection system | |
| CN103340637A (en) | System and method for driver alertness intelligent monitoring based on fusion of eye movement and brain waves | |
| CN101639894A (en) | Method for detecting train driver behavior and fatigue state on line and detection system thereof | |
| CN102110347A (en) | Equipment and method for detecting and alarming tumbling of human body | |
| CN109034111A (en) | A kind of driver's hand based on deep learning is from steering wheel detection method and system | |
| CN104269028A (en) | Fatigue driving detection method and system | |
| CN104068868A (en) | Method and device for monitoring driver fatigue on basis of machine vision | |
| CN107909772A (en) | A kind of intelligence vehicle-mounted fatigue monitoring method | |
| CN103236158B (en) | Method for warning traffic accidents in real time on basis of videos | |
| CN105708480A (en) | Driver attention testing device based on detection response task | |
| Jiang et al. | Driversonar: Fine-grained dangerous driving detection using active sonar | |
| CN103700220A (en) | Fatigue driving monitoring device | |
| CN108010269A (en) | A kind of driving based on car networking is divert one's attention monitoring, early warning system and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20110525 |