Intelligent human detection based on depth information

Tzu Wei Chen, Ku Ying Lin*, Yon Ping Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes an intelligent human detection system based on the depth information generated by Kinect to find out humans from a sequence of images and resolve occlusion problems. The system is divided into three parts, including region-of-interest (ROI) selection, feature extraction and human recognition. First, the histogram projection and connected component labeling are applied to select the ROIs according to the property that human would present vertically in general. Then, normalize the ROIs based on the distances between objects and camera and extract the human shape feature by the edge detection and distance transformation to obtain the distance image. Finally, the chamfer matching is used to search possible parts of the human body under component-based concept, and then shape recognition is implemented according to the combination ofparts of the human body. From the experimental results, the system could detect humans with high-accuracy rate and resolve occlusion problems.

Original languageEnglish
Title of host publicationProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PublisherMVA Organization
Pages286-289
Number of pages4
ISBN (Print)9784901122139
StatePublished - 2013
Event13th IAPR International Conference on Machine Vision Applications, MVA 2013 - Kyoto, Japan
Duration: 20 May 201323 May 2013

Publication series

NameProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013

Conference

Conference13th IAPR International Conference on Machine Vision Applications, MVA 2013
Country/TerritoryJapan
CityKyoto
Period20/05/1323/05/13

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