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Density crowd counting method based on HOG characteristic and color histogram characteristic

A technology of color histogram and crowd counting, applied in the research field of computer image processing and video surveillance

Inactive Publication Date: 2015-03-25
SUN YAT SEN UNIV
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Problems solved by technology

[0004] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art. The present invention has studied the method for counting people with density. Aiming at the research and analysis of various crowd counting methods at home and abroad, a method based on HOG features and color histogram is proposed. The density crowd counting method of graph features effectively solves the time and cost problems caused by manual monitoring, and also effectively improves the accuracy rate

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  • Density crowd counting method based on HOG characteristic and color histogram characteristic
  • Density crowd counting method based on HOG characteristic and color histogram characteristic
  • Density crowd counting method based on HOG characteristic and color histogram characteristic

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[0056] refer to figure 1 , is based on the HOG feature and color histogram feature of the density crowd counting method of head area recognition: including extracting HOG (Histograms of Oriented Gradients Gradient Histogram) features, training the first SVM (Support Vector Machine Support Vector Machine) classifier, and extract its color histogram features for the detection area that generates HOG features, and train a second SVM classifier. When detecting, first use the first SVM classifier for classification, and then use the second SVM classifier Carry out secondary classification, combine the detection scores of two SVM classifiers, and judge whether the detection area is a human head area; the specific method is as follows:

[0057] 1.1) Use the same sample set to train two SVM classifiers (hereinafter referred to as the first SVM classifier and the second SVM classifier), corresponding to HOG features and color histogram features;

[0058] 1.2) Use a window of 64*64 siz...

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Abstract

The invention discloses a density crowd counting method based on the HOG characteristic and the color histogram characteristic. The method includes the following steps that S1, the HOG characteristic of an acquired image region is extracted, and the color histogram characteristic of a detection window in which the HOG characteristic is generated is extracted; S2, a first SVM classifier is acquired based on HOG characteristic training, and a second SVM classifier is acquired based on color histogram characteristic training, wherein the first SVM classifier is used for pre-estimating a detection region, and the second SVM classifier is used for secondarily classifying the pre-estimated detection region; whether the detection region is a head region or not is determined by weighting and combining results acquired by the two SVM classifiers; S3, according to the detected head region, the number of crowds in a video can be counted through a region matching method based on an optical flow method. The density crowd counting method based on the HOG characteristic and the color histogram characteristic is good in accuracy and anti-interference performance.

Description

technical field [0001] The invention relates to the research fields of computer image processing and video monitoring, in particular to a method for counting density crowds based on HOG features and color histogram features. Background technique [0002] With the gradual popularization of video recording equipment, digital video data is growing explosively. Faced with such a large number of videos with such rich content, how to monitor video has become an urgent problem in the field of computer video; at the same time, due to statistical analysis technology and With the rapid development of video processing technology, the real-time intelligent crowd density monitoring system has become the focus of people's research. The HOG feature is a commonly used processing method in the video field. The HOG feature: Histogram of Oriented Gradient (HOG) feature is a feature descriptor used for object detection in computer vision and image processing. It forms features by calculating a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06M11/00
CPCG06V40/103G06V10/507G06F18/2411
Inventor 纪庆革陈青辉高静伟
Owner SUN YAT SEN UNIV
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