Fatigue detecting method based on individual learning

A fatigue detection and individual technology, which is applied in image fatigue detection, using the skin color segmentation algorithm to detect driver fatigue, can solve the problems of algorithm deviation and poor detection pertinence, and achieve the effect of improved detection accuracy and wide application prospects

Inactive Publication Date: 2015-07-29
NANJING UNIV
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Problems solved by technology

[0004] Purpose of the invention: the problem to be solved by the present invention is that the current fatigue detection algorithm is poorly targeted for th...

Method used

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  • Fatigue detecting method based on individual learning
  • Fatigue detecting method based on individual learning
  • Fatigue detecting method based on individual learning

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Embodiment Construction

[0030] The core idea of ​​the present invention is to use the learning of the characteristics of the eyes of the testee to achieve the effect of using targeted thresholds for different testees. Finally, fatigue was judged by the PERCLOS method.

[0031] like image 3 As shown, the present invention discloses a method for fatigue detection based on individual learning to improve the specificity and applicability of fatigue detection, comprising the following steps:

[0032] Step 1: Take a video of the subject through the acquisition device as a basis for learning and judgment, and frame the video at a relatively high frequency, so that each picture can approximately represent the instantaneous state of the face. Get enough sample images.

[0033] Step 2. Use the face segmentation method based on skin color to segment the face area of ​​all samples and determine the approximate distribution range of the eyes from the face distribution: preprocess the obtained sample image, con...

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Abstract

The invention discloses a fatigue detecting method based on individual learning. The method includes the following steps that (1) a video of face of a detected party is shot, and frame grabbing is performed on the video so that enough samples can be obtained; (2) human face area dividing is performed on all samples by means of a human face dividing method based on skin color and approximate distribution ranges of eyes are determined through human face distribution; (3) features of human eye ranges of all samples are extracted, a threshold value that is accurately adapted to opening and closing of eyes of the detected party is obtained, and detection in allusion to the detected party is performed with the threshold value as the standard; (4) whether the detected party is in a fatigue state or not is determined by means of the obtained threshold value and percentage of eyelid closure time (PERCLOS). By means of the fatigue detecting method based on individual learning, fatigue detection of the detected party is achieved by means of an adaptive learning method in allusion to eye ranges of the detected party, pertinence and accuracy of fatigue detection can be improved, and certain innovativeness is achieved.

Description

technical field [0001] The invention relates to the field of image fatigue detection, in particular to the field of driver fatigue detection using a skin color segmentation algorithm. Background technique [0002] Driver fatigue driving is one of the important causes of traffic accidents, ranking first among the causes of death in traffic accidents. With the increasing number of vehicles, fatigue driving has gradually become an important social problem. Therefore, the development of a fatigue driving detection system is of great significance for improving traffic safety and ensuring the safety of people's lives and property. [0003] Among the current fatigue detection algorithms, the most simple and effective one is the fatigue detection algorithm based on the PERCLOS algorithm, which mainly uses the skin color characteristics of the face and the geometric features of the face to locate the human eyes, and obtains whether the subject is fatigued or not by observing the huma...

Claims

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Application Information

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IPC IPC(8): G06K9/64G06T7/00
Inventor 袁杰孙方轩邱睿
Owner NANJING UNIV
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