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Front face human body automatic identity recognition method under long-distance video

An identity recognition and long-distance technology, applied in the field of pattern recognition, can solve the problems of staying in theory and unformed gait recognition system, and achieve the effect of improving recognition accuracy

Inactive Publication Date: 2010-03-03
HARBIN ENG UNIV
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Problems solved by technology

[0009] However, no gait recognition system has been formed so far, and existing research remains theoretical

Method used

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  • Front face human body automatic identity recognition method under long-distance video
  • Front face human body automatic identity recognition method under long-distance video
  • Front face human body automatic identity recognition method under long-distance video

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Embodiment Construction

[0027] The present invention is described in more detail below in conjunction with accompanying drawing example:

[0028] 1. Pedestrian detection and face detection

[0029] Pedestrian detection and face detection are implemented using Adaboost algorithm.

[0030] 1.1 Adaboost algorithm

[0031] Given a sample image set (x 1 ,y 1 ),..., (x n ,y n ), where y i ={0, 1} represent negative samples and positive samples, respectively. Initialize weights: respectively corresponding to y i = 0, the weight of 1 sample Among them, m and l represent the number of negative and positive samples respectively.

[0032] The process of Adaboost algorithm training is as follows:

[0033] (1) Weight normalization, For each feature j, construct a weak classifier h j , the maximum value F of the feature j distribution on the statistical sample set max (j) and the minimum value F min (j), let the exhaustive search threshold parameter θ j ∈[F min (j), F max (j)] such that h ...

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Abstract

The invention provides a front face human body automatic identity recognition method under a long-distance video. The method comprises a gait module and a human face module, and the method comprises the steps of firstly reading a video file, using the Adaboost method for detecting pedestrians, automatically opening the human face module and the gait module for respectively adopting the kernel principal component analysis on gait and human face for carrying out feature extraction if detecting the pedestrians, and finally adopting the decision-making level fusion method which adopts the human face features to assist the gait features for carrying out recognition. The method proposes a new solution concept for long-distance identity recognition and adopts the decision-making level fusion method which uses the human face features to assist the gait features. The human face features are assisted in the single-sample gait recognition, and the method has the advantages that even the gait training sample is the single sample and human face images are multiple, the number of the training samples can be expanded from another point of view, thereby being beneficial to the identity recognition, and improving the recognition precision by 2.4% by the fusion with the human face features.

Description

(1) Technical field [0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a gait recognition method. (2) Background technology [0002] In the HID program funded by the US Defense Advanced Research Projects Agency (DARPA) in 2000, many well-known institutions such as the University of Maryland, the Massachusetts Institute of Technology, and Carnegie Mellon University were involved. Its mission is to develop multi-modal, large-scale Visual monitoring technology can realize the detection, classification and identification of people at a long distance, so as to enhance the defense and civilian use against terrorist attacks. In addition, some universities and research institutions in Canada, Japan, Switzerland and other countries have also started active exploration in this area. Research in this area has also been carried out in China. The National Key Laboratory of Pattern Recognition (NLPR) of the Institute of Automation, Ch...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00A61B5/117A61B5/1171
Inventor 王科俊贲晛烨李欣王晨晖
Owner HARBIN ENG UNIV
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