CN202472864U - Driver fatigue early warning device - Google Patents
Driver fatigue early warning device Download PDFInfo
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- CN202472864U CN202472864U CN201220081530XU CN201220081530U CN202472864U CN 202472864 U CN202472864 U CN 202472864U CN 201220081530X U CN201220081530X U CN 201220081530XU CN 201220081530 U CN201220081530 U CN 201220081530U CN 202472864 U CN202472864 U CN 202472864U
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Abstract
The utility model discloses a driver fatigue early warning device, which comprises a photographic unit, a face capture detector, a living body identification device and an alarming device, wherein the photographic unit is used for acquiring the real-time video information of a driver; the face capture detector is connected with the photographic unit, and is used for receiving the video information acquired by the photographic unit, and judging whether the video information comprises a face or not; the living body identification device is connected with the photographic unit, and is used for receiving the video information acquired by the photographic unit, and judging whether the face in the video information is real or not; and the alarming device is connected with the face capture detector and the living body identification device, and is used for transmitting alarming information. According to the driver fatigue early warning device, the fatigue of the driver can be analyzed; and the device is high in identification accuracy, easy to upgrade and maintain and low in cost, and can stably work. The fatigued driving of the driver can be discovered and early warned, and a traffic accident caused by the fatigue driving can be effectively avoided.
Description
Technical field
The utility model belongs to the image recognition technology field, relates to a kind of fatigue early warning device, relates in particular to a kind of driver fatigue prior-warning device.
Background technology
Driving fatigue is meant the driver after the long-time continuous driving, the imbalance that produces physiological function and mental function, and the phenomenon that driving efficiency descends is objectively appearring.Driver's poor sleeping quality or deficiency, the long-duration driving vehicle occurs tired easily.Driving fatigue can have influence on driver's aspects such as attention, sensation, consciousness, thinking, judgement, will, decision and motion.Tired continued steering vehicle can be felt sleepy drowsiness, weakness of limbs; Absent minded, judgement descends, even occurs absent-minded or moment memory disappearance; Occur that action is delayed or too early, road traffic accident very easily takes place in unsafe factor such as operation pauses or the correction time is improper.Therefore, forbid steering vehicle after the fatigue.
Form the main cause of driving fatigue:
1. living environment: the residence is far away excessively far from the work place; Matter in home is too much or the man and wife is inharmonious; Mental burden is heavy; Social activity is too wide, and the participation recreational activities time is oversize.
2. sleep quality: went to bed evening, the length of one's sleep very little; Sleeper effect is poor; Noisy sleep environment can not guarantee sleep quality.
3. environment inside car: air quality is poor, improper ventilation; Too high or too low for temperature; Noise and serious vibration; The seat adjustment is improper; With nervous with the car relationship.
4. car external environment: in the afternoon, at dusk, morning, the driving of period in the late into the night; Pavement behavior is poor; Road conditions is good, and situation is single; Dust storm, rain, mist, the driving of snow weather; Traffic environment difference or transportation condition are crowded.
5. service condition: long-time, long distance driving; The speed of a motor vehicle is too fast or slow excessively; Too restriction arrives the time of destination.
6. physical qualification: muscle power, endurance are poor; The ability of looking, listen descends; Muscle power is weak or suffer from certain chronic disease; Take steering vehicle and avoid the medicine of usefulness; Female pathology particular time (menstrual period, pregnancy period).
7. drive experience: technical merit is low, operation is not familiar; Short, lack of experience of driving time; Awareness of safety is poor.
How in time to find fatigue driving; How under the situation of finding fatigue driving, carry out early warning effectively, thereby avoid all kinds of traffic hazards that cause by fatigue driving? These queries have become the problem that nowadays presses for solution.
The utility model content
The utility model technical matters to be solved is: a kind of driver fatigue prior-warning device is provided, can finds driver tired driving and early warning in time, can avoid the traffic hazard that is caused by fatigue driving effectively.
For solving the problems of the technologies described above, the utility model adopts following technical scheme:
A kind of driver fatigue prior-warning device, said device comprises:
Image unit is in order to obtain driver's real-time video information;
People's face is caught detector, connects said image unit, in order to receiving the video information that image unit obtains, and judges whether people's face is wherein arranged;
The vivo identification device connects said image unit, in order to receiving the video information that image unit obtains, and judges whether the people's face in the video information is real;
Warning device is connected with said people's face seizure detector, vivo identification device, in order to send warning message.
As a kind of preferred version of the utility model, said device further comprises:
The human face posture recognition device connects said image unit, in order to receive the video information that image unit obtains, the front face in the video is detected in real time, confirms the position of people's face in image, judges whether human face posture is safe attitude;
Whether people's face attributive analysis device connects said image unit, in order to receive the video information that image unit obtains, driver's video image is passed to AdaBoost neural network classifier unit adjudicate tired.
As a kind of preferred version of the utility model, said warning device comprises the audible alarm unit.
As a kind of preferred version of the utility model, said image unit is a video camera.
The beneficial effect of the utility model is: the driver fatigue prior-warning device that the utility model proposes; Can analyze driver's fatigue strength; Have the recognition accuracy of enough highlands, can good compatibility accomplish early warning in time with existing monitor network, and working stability; Be easy to upgrading and safeguard that cost is low.The utility model can be found driver tired driving and early warning in time, can avoid the traffic hazard that is caused by fatigue driving effectively.
Description of drawings
Fig. 1 is the composition synoptic diagram of the utility model driver fatigue prior-warning device.
Embodiment
Specify the preferred embodiment of the utility model below in conjunction with accompanying drawing.
Embodiment one
See also Fig. 1; The utility model has disclosed a kind of driver fatigue prior-warning device, and said device comprises: image unit 10, people's face are caught detector 20, vivo identification device 30, human face posture recognition device 40, people's face attributive analysis device 50, warning device 60; Image unit 10, warning device 60 connect people's face respectively and catch detector 20, vivo identification device 30, human face posture recognition device 40, people's face attributive analysis device 50.
People's face is caught the video information that detector 20 obtains in order to the reception image unit, and judges whether people's face is wherein arranged.
The video information that vivo identification device 30 obtains in order to the reception image unit, and judge whether the people's face in the video information is real.
Human face posture recognition device 40 detects the front face in the video in order to receive the video information that image unit obtains in real time, confirms the position of people's face in image, judges whether human face posture is safe attitude.
Whether people's face attributive analysis device 50 is passed to AdaBoost neural network classifier unit with driver's video image and is adjudicated tired in order to receive the video information that image unit obtains.
The utility model device is installed in the position of departing from the place ahead, normal driving position 15 degree, as: on panel board, console top or the vehicle body front pillar, or embedded device is integrated.This device can be caught the driver and driven attitude in real time, and four detection modules are arranged in the device, and when wherein any one module made a mistake, system will carry out the early warning operation automatically.
More than be the composition of the utility model driver fatigue prior-warning device, the tired method for early warning of the utility model device comprises the steps:
Step 1, obtain the driver through camera and drive video in real time.
Step 2, the video information that camera is obtained are imported in people's face pick-up unit (people's face is caught detector 20).Through people's face pick-up unit driver's real time video image is carried out recognition of face,, can trigger prior-warning device so and in time carry out early warning as finding that nobody's face exists in the video.
Step 3, human face posture recognition device also can be called people's face locating device, align the dough figurine face and detect in real time, confirm the position of people's face in image; Be included as feature calculation unit and taxon; Described for feature calculation unit is that gray level image to be detected is carried out convergent-divergent, thus judge whether human face posture is aftereffect attitude safely.
Step 4, vivo identification device receive the video information that image unit obtains, and judge whether the people's face in the video information is real.The effect of vivo identification is exactly to avoid being guaranteed that by photo, video recording deception real human face is captured.
Step 5, final step judge exactly whether the driver is in fatigue driving.Driver's video image is passed to AdaBoost neural network classifier unit adjudicates; Through two of drivers' closure is judged; When the eyes closed time surpasses 2.5 seconds, just assert that this driver is fatigue driving, device can trigger warning system automatically.
Step 6, step 2, any one device detects the situation that fatigue driving exists in 3,4,5, all can touch warning device and carry out early warning in time.
The characteristics of the utility model: 1, misclassification rate is low; 2, the fatigue strength judging nicety rate is high; 3, early warning is timely.
In sum, the driver fatigue prior-warning device that the utility model proposes can be analyzed driver's fatigue strength; Have the recognition accuracy of enough highlands, can good compatibility accomplish early warning in time with existing monitor network, and working stability; Be easy to upgrading and safeguard that cost is low.The utility model can be found driver tired driving and early warning in time, can avoid the traffic hazard that is caused by fatigue driving effectively.
Here description of the utility model and application is illustrative, is not to want the scope of the utility model is limited in the above-described embodiments.Here the distortion of the embodiment that is disclosed and change are possible, and the replacement of embodiment is known with the various parts of equivalence for those those of ordinary skill in the art.Those skilled in the art are noted that under the situation of spirit that does not break away from the utility model or essential characteristic, and the utility model can be with other form, structure, layout, ratio, and realize with other assembly, material and parts.Under the situation that does not break away from the utility model scope and spirit, can carry out other distortion and change here to the embodiment that is disclosed.
Claims (4)
1. a driver fatigue prior-warning device is characterized in that, said device comprises:
Image unit is in order to obtain driver's real-time video information;
People's face is caught detector, connects said image unit, in order to receiving the video information that image unit obtains, and judges whether people's face is wherein arranged;
The vivo identification device connects said image unit, in order to receiving the video information that image unit obtains, and judges whether the people's face in the video information is real;
Warning device is connected with said people's face seizure detector, vivo identification device, in order to send warning message.
2. driver fatigue prior-warning device according to claim 1 is characterized in that:
Said device further comprises:
The human face posture recognition device connects said image unit, in order to receive the video information that image unit obtains, the front face in the video is detected in real time, confirms the position of people's face in image, judges whether human face posture is safe attitude;
Whether people's face attributive analysis device connects said image unit, in order to receive the video information that image unit obtains, driver's video image is passed to AdaBoost neural network classifier unit adjudicate tired.
3. driver fatigue prior-warning device according to claim 1 is characterized in that:
Said warning device comprises the audible alarm unit.
4. driver fatigue prior-warning device according to claim 1 is characterized in that:
Said image unit is a video camera.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201220081530XU CN202472864U (en) | 2012-03-06 | 2012-03-06 | Driver fatigue early warning device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201220081530XU CN202472864U (en) | 2012-03-06 | 2012-03-06 | Driver fatigue early warning device |
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| Publication Number | Publication Date |
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| CN202472864U true CN202472864U (en) | 2012-10-03 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201220081530XU Expired - Lifetime CN202472864U (en) | 2012-03-06 | 2012-03-06 | Driver fatigue early warning device |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103310590A (en) * | 2012-03-06 | 2013-09-18 | 上海骏聿数码科技有限公司 | System and method for driver fatigue analysis and early-warning |
| CN106447583A (en) * | 2016-09-12 | 2017-02-22 | 四川长虹电器股份有限公司 | Drug driving early warning system and method based on intelligent mobile terminal |
| CN107832669A (en) * | 2017-10-11 | 2018-03-23 | 广东欧珀移动通信有限公司 | Method for detecting human face and Related product |
| CN110188645A (en) * | 2019-05-22 | 2019-08-30 | 北京百度网讯科技有限公司 | For the method for detecting human face of vehicle-mounted scene, device, vehicle and storage medium |
-
2012
- 2012-03-06 CN CN201220081530XU patent/CN202472864U/en not_active Expired - Lifetime
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103310590A (en) * | 2012-03-06 | 2013-09-18 | 上海骏聿数码科技有限公司 | System and method for driver fatigue analysis and early-warning |
| CN106447583A (en) * | 2016-09-12 | 2017-02-22 | 四川长虹电器股份有限公司 | Drug driving early warning system and method based on intelligent mobile terminal |
| CN107832669A (en) * | 2017-10-11 | 2018-03-23 | 广东欧珀移动通信有限公司 | Method for detecting human face and Related product |
| CN107832669B (en) * | 2017-10-11 | 2021-09-14 | Oppo广东移动通信有限公司 | Face detection method and related product |
| CN110188645A (en) * | 2019-05-22 | 2019-08-30 | 北京百度网讯科技有限公司 | For the method for detecting human face of vehicle-mounted scene, device, vehicle and storage medium |
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| C14 | Grant of patent or utility model | ||
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| CX01 | Expiry of patent term |
Granted publication date: 20121003 |