Multi-feature fusion pedestrian detection method based on HIKSVM classifier

A multi-feature fusion and pedestrian detection technology, applied in the field of computer vision and pattern recognition, can solve the problems of poor real-time detection and low detection accuracy, and achieve the effect of overcoming poor practicability, strong robustness and improving real-time performance.

Active Publication Date: 2018-04-06
CHINA UNIV OF MINING & TECH
View PDF6 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In view of the above analysis, the present invention aims to provide a pedestrian detection method based on the multi-feature fusion o

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multi-feature fusion pedestrian detection method based on HIKSVM classifier
  • Multi-feature fusion pedestrian detection method based on HIKSVM classifier
  • Multi-feature fusion pedestrian detection method based on HIKSVM classifier

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0059] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and together with the embodiments of the present invention are used to explain the principle of the present invention and are not intended to limit the scope of the present invention.

[0060] A specific embodiment of the present invention discloses a pedestrian detection method based on the multi-feature fusion of the HIKSVM classifier, such as figure 1 As shown, it specifically includes the following steps:

[0061] Step S1, determining the behavior area in the pedestrian image sequence;

[0062] Transform the scale of the pedestrian image sequence to be detected to a uniform size, and detect the behavior area.

[0063] Optionally, the sequence of images of pedestrians to be detected can be preprocessed to obtain clearer images and improve the accuracy of image detection....

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention relates to a multi-feature fusion pedestrian detection method based on an HIKSVM classifier. The method concretely comprises the following steps of: determining a behavior area in a pedestrian image sequence; extracting multi-item features in the behavior area, and forming fusion features; and employing a trained HIKSVM classifier based on the fusion features to perform pedestrian detection. The method provided by the invention improves a feature extraction method, after HOG features are extracted, a gradient field is changed to an optical flow field through analogy, andHOF features are extracted, shape information and motion information of an object are retained, so that computation complexity of describing a full-size moving object by employing the optical flow field is avoided and the robustness is high; an LBP algorithm is improved to extract texture features through adoption of an LQC algorithm, so that the computation complexity is reduced on the basis without losing texture information; and a histogram intersection kernel (HIK) and an intersection coordinate drop method are employed to perform classification training of the SVM classifier, so that thecomputation complexity is low and the detection precision is high.

Description

technical field [0001] The invention relates to the technical fields of computer vision and pattern recognition, in particular to a pedestrian detection method based on multi-feature fusion of a HIKSVM classifier. Background technique [0002] Pedestrian detection is a challenging task due to their high variability in appearance and wide variety of poses. A robust feature set is crucial for correctly distinguishing pedestrians if one wants to correctly detect humans in cluttered backgrounds or under difficult lighting conditions. [0003] For the problem of pedestrian detection, many descriptors for feature extraction have been proposed. Among them, the Histogram of Oriented Gradients (HOG) descriptor provides superior performance relative to other feature sets, including wavelets. However, the gradient direction histogram represents the edge information of the image, and retains the shape information of the target. It is aimed at a single image, but pedestrian detection i...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/10G06F18/2411G06F18/253
Inventor 程德强冯晨晨唐世轩赵凯寇旗旗李岩蔡迎春刘海
Owner CHINA UNIV OF MINING & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap