Human body detecting method based on SURF (Speed Up Robust Feature) efficient matching kernel

A high-efficiency technology for human detection, applied in the field of image processing, can solve problems such as insufficient light, mixed background, and a lot of training data, and achieve the effect of low dimensionality, reducing feature extraction time and data calculation amount

Inactive Publication Date: 2012-12-05
XIDIAN UNIV
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The advantage of the method based on statistical classification is that the detection results are stable and the effect is good. The disadv

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  • Human body detecting method based on SURF (Speed Up Robust Feature) efficient matching kernel
  • Human body detecting method based on SURF (Speed Up Robust Feature) efficient matching kernel
  • Human body detecting method based on SURF (Speed Up Robust Feature) efficient matching kernel

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Embodiment Construction

[0027] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0028] Step 1: From the INRIA database of the French National Institute of Information and Automation, a large number of negative sample images are obtained through the bootstrap operation, and form a training sample set together with other positive sample images in the database, where the negative sample images are as follows: figure 2 As shown, the positive sample image is as image 3 shown.

[0029] Step 2, extract the SURF descriptor feature point F of the training sample set.

[0030] 2a) Divide the j-th training image into 8×8 pixel grids, each grid is sampled according to the image scale of 16 and 25 pixels, and obtain the SURF Speed ​​Up Robust Feature description sub-feature point F of the i-th training image j ;

[0031] 2b) According to step 2a), extract the SURF descriptor feature points F of all training images, where F={F 1 ...,F j ...,F N},j∈[1,M], M i...

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Abstract

The invention provides a human body detecting method based on an SURF efficient matching kernel, and mainly solves the problem that image background hybridity can not be better processed in the existing method. The method comprises the steps that a negative sample is obtained through bootstrap in an INRIA (Institute National de Recherce en Informatique et Automatique) database, and a training sample set of the whole human body is formed by the negative sample and a positive sample in the database; SURF descriptor feature points are extracted under different image scales for the training sample; feature points are extracted by random sampling to constitute the initial vector basis of a visual vocabulary; constrained singular value decomposition is utilized for the initial vector basis to obtain the maximum kernel function feature; the maximum kernel function feature in different image scales is weighted to obtain the features under all the image scales; the obtained features are trained in different classes by an SVM (Support Vector Machine) classifier, and a detection classifier is obtained; and the image to be detected is input to the classifier to obtain the final detection result. The method disclosed by the invention can be used for accurately detecting the human body, and can be used for intelligent monitoring, driver auxiliary systems and virtual video.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to a static human body detection method, and can be used for intelligent monitoring, driver assistance systems, human body motion capture, pornographic image filtering and virtual video. Background technique [0002] In the field of computer vision, human body detection is a technology with very broad application prospects. Various factors such as occlusion make human detection a very difficult problem. At present, the methods of human detection in static images mainly include detection methods based on motion characteristics, methods based on human body models and methods based on statistical classification. [0003] The detection method based on motion characteristics is to use the posture change of the human body when it is stable and the symmetry of the human body to change periodically, construct a self-similar matrix in the time domain, and reflect the difference from othe...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 韩红王瑞谢福强李晓君顾建银张红蕾韩启强刘三军郭玉言甘露
Owner XIDIAN UNIV
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