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System and method for human detection and counting using background modeling, hog and haar features
System and method for human detection and counting using background modeling, hog and haar features
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机译：使用背景建模，猪和哈尔特征进行人类检测和计数的系统和方法
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摘要
A system for adaptive learning based human detection for channel input of captured human image signals, the said system comprises of: a sensor for tracking real time images of environment of interest; a feature extraction and classifiers generation means for extracting a plurality of the features and classifying the features associated with time-space descriptors of image comprising background modeling, Histogram of Oriented Gradients (HOG) and Haar like wavelet; a processor configured to process extracted feature classifiers associated with plurality of real-time images; a means for combining plurality of feature classifiers of time-space descriptors; a means for evaluating linear probability of human detection based on predetermined threshold value of feature classifier in a time window having at least one image frame; a counter for counting the number of human in the image; and a transmission means adapted to send the final human detection decision and number thereof to storage means.
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