Human detection method

A technology of human body detection and detection models, which is applied in the fields of computer vision and image processing, and can solve problems such as complex backgrounds, occlusions, and different clothing

Active Publication Date: 2013-12-25
TIANJIN UNIV
View PDF1 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the human body detection method based on color images still has some limitations, including: (a) different clothes, different postures; (b) changes in illumination; (c) complex background; (d) occlusion problems, etc.

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
  • Human detection method
  • Human detection method
  • Human detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0032] In recent years, with the emergence of depth cameras such as TOF and Kinect, it has become easier to obtain depth maps. The depth map records depth information through infrared detection and other technologies, which overcomes the influence caused by changes in illumination and different colors of clothing. At the same time, because the depth information at the edge changes significantly, the edge information features can be enhanced through the depth change information, making the detection result more precise. Therefore, the embodiment of the present invention provides a human body detection method combining color and depth information, see figure 1 , see the description below:

[0033] 101: Combine color and depth informati...

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 invention discloses a human detection method. The human detection method includes the following steps that gradient histogram features are extracted in the depth color direction by the cooperation of color information with depth information; detection models are trained; region segmentation is conducted on test images, and the images are detected based on a segmentation result to obtain a candidate region (SR); the candidate region (SR) is verified based on edge detection. The human detection method based on color information and depth information is achieved, the obtained features comprise color information and depth information by the cooperation of feature extraction, outline edge information is enhanced, and then the features are more representative. Detection strategies based on different features and different classification models are used for different parts, and the defect that accuracy of long-distance objects shot by a depth camera is low is overcome. The verification method based on edge information is adopted, and then the detection result is more accurate.

Description

technical field [0001] The invention relates to the fields of image processing and computer vision, in particular to a method for human body detection using color and depth information in an RGB-D (color depth) image taken by Kinect. Background technique [0002] Human detection technology is one of the research hotspots in the field of image processing and computer vision, and it has been widely used in many aspects, such as: traffic safety, community monitoring and robotics. In order to obtain ideal detection results, many researchers have conducted in-depth research on feature extraction, classifier training, etc., and proposed many solutions. [0003] Most existing human detection methods are based on color images. The process of human detection is mainly divided into two steps, one is to extract effective features, and the other is to train a powerful classifier. For feature extraction, existing color image features include histogram of oriented gradients (HOG), LBP (...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/66
Inventor 雷建军范晓红由磊侯春萍李实秋张翠翠
Owner TIANJIN UNIV
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