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A Driver Abnormal Behavior Detection Method Based on Online Behavior Modeling

A detection method and driver's technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of less abnormal behavior, large model problems, and insufficient real data, etc., and achieve less error rate and increased stability sexual effect

Inactive Publication Date: 2018-07-17
CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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Problems solved by technology

Therefore, existing technologies are basically divided into two categories: one is to detect only a specific abnormal behavior, this method only detects fatigue driving behavior, but the specific performance of abnormal behavior of different drivers may be different; the other The reason is that the training method is single. Due to the small number of abnormal behaviors and the difficulty of sample collection, most of the solutions use artificially simulated data for offline training, but the simulated data is usually not real enough, so the trained model is in There is a greater possibility of problems during use, which also makes it difficult to use offline training methods

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  • A Driver Abnormal Behavior Detection Method Based on Online Behavior Modeling
  • A Driver Abnormal Behavior Detection Method Based on Online Behavior Modeling
  • A Driver Abnormal Behavior Detection Method Based on Online Behavior Modeling

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Embodiment Construction

[0039] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0040] Based on the method of detecting foreground through background modeling in video analysis technology, the present invention proposes a method for detecting abnormal driver behavior based on online behavior modeling, which detects the driver by modeling the normal behavior of the driver abnormal behavior.

[0041] This method takes into account the following situations: (1) most of the driver's behaviors are normal behaviors, and only a few behaviors are abnormal; (2) normal behaviors and abnormal behaviors are separable in the feature space. Therefore, assuming that most of the input data belongs to the category of normal behavior, the data of the normal behavior category is modeled, so that a small number of abnormal behaviors can be judged by whether they satisfy the normal behavior model.

[0042] The main idea of ​​the method is...

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Abstract

The invention relates to a driver abnormal behavior detection method based on online behavior modeling, and belongs to the technical field of image recognition and monitoring. Based on video analysis technology, the method detects the abnormal behavior of the driver by modeling the normal behavior of the driver. It mainly includes the following steps: 1. Initialization, establishing an initial model or updating the existing model; 2. The driver's behavior is extracted; 3. Combining the initial model and the driver's behavior characteristics to judge whether the driver's behavior is normal; 4. Updating the model. The present invention provides a method for detecting abnormal driver behavior based on online behavior modeling, which uses novelty detection to detect abnormal behavior, and adopts a multi-modal modeling method to process various normal behaviors and various abnormal behaviors , supplemented by the method of manual labeling to eliminate false alarms, which increases the stability of the scheme and reduces the error rate of the scheme.

Description

technical field [0001] The invention relates to a method for detecting abnormal behavior of a driver, in particular to a method for detecting abnormal behavior of a driver based on online behavior modeling. Background technique [0002] Vehicle-mounted vision system has become an emerging application direction in the field of image processing and video analysis. The research on abnormal behavior detection of drivers belongs to the field of intelligent transportation and is a key technology of intelligent assisted driving. This technology detects abnormal behavior of drivers and sends out Warning, to avoid traffic accidents, has important application value and social significance. [0003] At this stage, the research and development in this field in many countries at home and abroad are limited by the characteristics of abnormal behaviors. For example, there are many types of abnormal behaviors, including driver fatigue behaviors such as closing eyes for a long time, yawning,...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/21
Inventor 李远钱周曦周祥东石宇颜卓
Owner CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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