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Pedestrian abnormity identification method based on probabilistic latent semantic analysis

A technology of semantic analysis and abnormal recognition, applied in the field of pattern recognition, can solve problems such as performance degradation and no longer applicable, and achieve the effect of improving accuracy, strong adaptability, and improving the correct rate of recognition

Inactive Publication Date: 2017-05-10
JIANGSU XINTONGDA ELECTRONICS SCI & TECHCO
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Problems solved by technology

However, these early studies were limited to human action recognition in restricted scenes, such as specific perspectives, action figures, backgrounds, and lighting. In natural scenes, when the above-mentioned restrictions were removed, the performance of the method dropped sharply or even no longer applicable

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  • Pedestrian abnormity identification method based on probabilistic latent semantic analysis
  • Pedestrian abnormity identification method based on probabilistic latent semantic analysis
  • Pedestrian abnormity identification method based on probabilistic latent semantic analysis

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Embodiment Construction

[0040] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0041] In order to improve the accuracy of action recognition, an example of the present invention provides a method for identifying abnormal pedestrians based on probabilistic latent semantic analysis. See the following description for details:

[0042] Step A, create a database.

[0043] The test database used in this method is the CASIA (Institute of Automation, Chinese Academy of Sciences) behavior analysis database, which is formed by shooting from cameras distributed in three different viewing angles in an outdoor environment, and provides experimental data for behavior analysis. The data is...

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Abstract

The invention provides a pedestrian abnormity identification method based on probabilistic latent semantic analysis, which is mainly used for solving the problems of poor feature representation capability and not accurate classification in the prior art. The method comprises the following steps: extracting a human body moving object from a video file; extracting space-time interest points in an object region, and representing the space-time interest points through HOG3D / HOF descriptors; carrying out classification on all descriptor feature vectors through a K-means clustering method, generating video dictionary and establishing a bag-of-word model; and then, training a probabilistic latent semantic analysis model to realize classification of test videos. The method can accurately identify human body motion, has a certain robustness for environment scene motion and human body shape change, can be used for pedestrian video monitoring.

Description

[0001] Technical Field: The present invention relates to a method for human behavior recognition using computer vision, specifically a method for classifying human behavior in a video to be analyzed, which belongs to the field of pattern recognition technology. [0002] technical background: [0003] Human behavior recognition is one of the major hotspots in the field of computer vision in recent years. It has been initially applied in many fields such as motion capture video surveillance, and has great application prospects. Due to the variability and diversity of human motion, background noise and background motion, many factors seriously affect the recognition effect of human motion. Realizing human behavior recognition is a long-standing problem in the field of computer vision. [0004] In the problem of human action recognition, researchers are often interested in pixels whose image intensity values ​​vary significantly in a local range. These "interest points" are usually ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/20G06V20/41G06F18/23213G06F18/241
Inventor 余国刚顾丽军彭伟鸿惠志洲戴小荣巢文科
Owner JIANGSU XINTONGDA ELECTRONICS SCI & TECHCO
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