Behavior recognition method based on depth and RGB information and multi-scale and multidirectional rank and level characteristics

A recognition method and multi-scale technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as performance degradation and unstable recognition performance, and achieve improved accuracy, improved adaptability, and good robustness and distinguishing effects

Active Publication Date: 2013-09-11
北京阿叟阿巴科技有限公司
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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the recognition performance of the behavior recognition method based on visible light is unstable. When the light changes greatly, for example, at night, its performance will drop sharply. A method based on depth and RGB information and multi-scale multi- A behavior recognition method based on directional, hierarchical, and hierarchical features is used to identify target behaviors in video surveillance, so as to realize intelligent analysis of surveillance videos

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  • Behavior recognition method based on depth and RGB information and multi-scale and multidirectional rank and level characteristics
  • Behavior recognition method based on depth and RGB information and multi-scale and multidirectional rank and level characteristics
  • Behavior recognition method based on depth and RGB information and multi-scale and multidirectional rank and level characteristics

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Embodiment 1

[0032] Such as figure 1 As shown, it is an operation flow chart of the behavior recognition method based on depth and RGB information and multi-scale, multi-directional and hierarchical features of the present invention. The operation steps of the method include:

[0033] Step 01 Video preprocessing

[0034] Filter and denoise the input depth and RGB image sequences. At the same time, through the infrared device of the Kinect device, the approximate distance between the target and the camera can be measured. According to the distance value, add 0.5 to obtain a large threshold, and subtract 1 to obtain a small threshold. For example, in the real-time example, the distance between the target and the camera is about 2 meters, the maximum threshold is 2.5 meters, and the minimum threshold is 1 meter. When the depth value of a pixel is greater than the maximum threshold or less than the minimum threshold, the pixel is marked as 0, otherwise it is marked as 1, so that the interf...

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Abstract

The invention discloses a behavior recognition method based on depth and RGB information and multi-scale and multidirectional rank and level characteristics. The behavior recognition method comprises steps of: video preprocessing, target motion changing process description, multi-scale and multidirectional rank and level characteristic extracting, model constructing, and model selection and deduction. By means of the behavior recognition method, depth images are used for performing behavior recognition so as to overcome difficulties occurred in visible light image behavior recognition, like interference of lighting changing, shadows, object shielding and the like; secondarily, by means of the method, depth difference value motion historical images and depth limitation RGB image difference value historical images can well capture human body behavior changing processes in image sequences and RGB image sequences, thirdly, the multi-scale and multidirectional rank and level characteristics disclosed by the method have space resolution capability and detail description capability and have good robustness and distinguishing performance; finally, models can be selected independently according to degree of light, and adaptability of a behavior recognition algorithm can be further improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision and pattern recognition, and relates to a behavior recognition method based on depth and RGB information and multi-scale, multi-directional, hierarchical and hierarchical features, which solves the difficulty of using visible light images for behavior recognition, and improves the accuracy and accuracy of behavior recognition. Robustness, it can be used to recognize the behavior of human targets in surveillance videos and realize intelligent management of surveillance videos. Background technique [0002] With the development of computer technology and information technology, the demand for video-based human behavior analysis is becoming more and more urgent. Behavior analysis plays an increasingly important role in systems such as intelligent monitoring, home security, intelligent robots, and athlete auxiliary training. role. However, most of the early human behavior recognition uses or...

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
Inventor 高赞申晓霞张桦薛彦兵徐光平
Owner 北京阿叟阿巴科技有限公司
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