Tree-shaped assembled classification method for pedestrian detection

A pedestrian detection, tree-like technology, applied in the field of intelligent transportation, can solve problems such as unbalanced samples, and achieve the effect of improving the accuracy, improving the detection speed, and reducing the difficulty of classification

Inactive Publication Date: 2008-10-22
UNIV OF SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem of unbalanced samples and detection speed in the pedestrian detection system, the present invention proposes a method for dynamically generating a tree-like combination classifier according to the principle of divide and conquer and

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  • Tree-shaped assembled classification method for pedestrian detection
  • Tree-shaped assembled classification method for pedestrian detection
  • Tree-shaped assembled classification method for pedestrian detection

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Embodiment Construction

[0023] The invention proposes a tree combination classifier method. The design idea is: follow the principle of divide and conquer and gradually refine. On the one hand, according to the imbalance of positive and negative objects in this background (in a general scene, each frame contains 20,000 objects, of which pedestrians only account for 2%), apply the principle of gradual refinement and follow the principle of "early rejection" Ensure the speed of classification and low false positive rate; on the other hand, apply the idea of ​​​​divide and conquer, further subdivide pedestrians into sub-categories, and divide complex classification problems into multiple simple sub-problems, thereby improving the accuracy of classification.

[0024] The structure of the combined classifier is a tree, and each node in the tree is a single classifier, and the single classifier is trained using the AdaBoost method. In this tree, the single classifier at the upper level can roughly disting...

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Abstract

The invention provides a method for dynamically generating a tree-shaped combination classifier, which is used to test walkers. The method comprises the following steps that: all samples are read in and have characteristics picked up, and characteristic vectors are generated; the tree-shaped combination classifier is initialized, which makes the structure as a tree with only one root node; whether extensible leaf nodes are existed in the tree is judged; one extensible leaf node is chosen to be a father node of a training single classifier, and a training sample is chosen for the training single classifier; a single classifier is obtained by the AdaBoos algorithm; whether the classifier obtained by training meets the fissionable requirement is judged, if the classifier fails to meet the fissionable requirement, the classifier is added in the tree; the sample used to train the single classifier is divided into two parts for retraining, and two single classifiers are obtained and added in the tree; the combination classifier is constructed until the classifier meets the requirement; the tree-shaped combination classifier obtained is utilized to classify testing targets, and testing results are obtained. The method of the invention has the advantages of lowering the rate of false alarm and improving the testing rate.

Description

technical field [0001] The invention relates to a pedestrian detection system under the concept of intelligent transportation, which belongs to the field of intelligent transportation. Background technique [0002] In recent years, my country's road traffic accidents have shown a rapid growth trend, of which urban traffic accidents account for the main part. In view of the characteristics of complex scenes, numerous pedestrians and vulnerability in urban traffic, pedestrian safety protection is the key to urban traffic safety. For this reason, Pedestrian Detection System (PDS: Pedestrian Detection System) has become a key technology of great concern to the research and industry circles. [0003] Classification-based pedestrian detection methods are currently the mainstream technology. The classifier is required to meet the following three conditions at the same time: (1) not affected by sample imbalance; (2) high accuracy; (3) fast classification. However, the commonly us...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 曹先彬许言午郭圆平魏闯先嘉晓岚吴培
Owner UNIV OF SCI & TECH OF CHINA
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