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2.5D multi-view gait recognition based on point cloud registration
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Tang, Jin, Luo, Jian, Tjahjadi, Tardi and Gao, Yan (2014) 2.5D multi-view gait recognition based on point cloud registration. Sensors, Volume 14 (Number 4). pp. 6124-6143. doi:10.3390/s140406124 ISSN 1424-8220.
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Official URL: http://dx.doi.org/10.3390/s140406124
Abstract
This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QA Mathematics T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
Library of Congress Subject Headings (LCSH): | Gait in humans -- Mathematical models, Human body -- Mathematical models, Computer vision | ||||||||
Journal or Publication Title: | Sensors | ||||||||
Publisher: | MDPI AG | ||||||||
ISSN: | 1424-8220 | ||||||||
Official Date: | 24 March 2014 | ||||||||
Dates: |
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Volume: | Volume 14 | ||||||||
Number: | Number 4 | ||||||||
Page Range: | pp. 6124-6143 | ||||||||
DOI: | 10.3390/s140406124 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 27 December 2015 | ||||||||
Date of first compliant Open Access: | 27 December 2015 | ||||||||
Funder: | Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC), Hunan, China (Province). Science and Technology Program | ||||||||
Grant number: | 91220301 (NNSFC), 2013WK3026 (Hunan) |
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