Person re-identification using appearance

The aim of this project is to apply a person re-identification algorithm which uses trivial appearance cues like color and texture, and achieve satisfactory performance without train- ing, on various datasets being used by the lab. Firstly, a literature review was done and the tracking results were...

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Main Author: Chikersal, Prerna
Other Authors: Qian Kemao
Format: Industrial Attachment (IA)
Language:English
Published: 2014
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Online Access:http://hdl.handle.net/10356/61790
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-617902023-03-03T20:55:45Z Person re-identification using appearance Chikersal, Prerna Qian Kemao School of Computer Engineering Computer Vision Laboratory, EPFL, Switzerland DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition The aim of this project is to apply a person re-identification algorithm which uses trivial appearance cues like color and texture, and achieve satisfactory performance without train- ing, on various datasets being used by the lab. Firstly, a literature review was done and the tracking results were visualised. After this, we explored three methods - (i) dominant colors, (ii) color histograms and (iii) color invariants for person re-identification. We applied these methods on two sports datasets - a volleyball sequence and a soccer sequence, and on one pedestrian dataset - a video shot in the lab at EPFL. Based on the accuracies calculated, we concluded that the signatures used in the color invariants method produce the best re- sults, since they are parts-based signatures or signatures which take spacial information into account. The dominant colors and color histograms methods do not work very well, since they are holistic approaches. Usually, the color histograms approach gives better results than the dominant colors approach, however, dominant colors can work better in a situa- tion where the illumination changes are not much and consistent dominant colors can be obtained to describe a person or team. , like in the soccer dataset. Person re-identification based on appearance is a challenging problem, which works better if the clothes worn by the different people to be re-identified are very different in color and/or texture. In future, it would be interesting to see if superpixels can be used to divide the person into meaningful parts which can then be matched for person re-identification. Finally, the reports ends with acknowledgement and a synopsis of my personal experience. 2014-10-10T01:32:25Z 2014-10-10T01:32:25Z 2014 2014 Industrial Attachment (IA) http://hdl.handle.net/10356/61790 en Nanyang Technological University 20 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Chikersal, Prerna
Person re-identification using appearance
description The aim of this project is to apply a person re-identification algorithm which uses trivial appearance cues like color and texture, and achieve satisfactory performance without train- ing, on various datasets being used by the lab. Firstly, a literature review was done and the tracking results were visualised. After this, we explored three methods - (i) dominant colors, (ii) color histograms and (iii) color invariants for person re-identification. We applied these methods on two sports datasets - a volleyball sequence and a soccer sequence, and on one pedestrian dataset - a video shot in the lab at EPFL. Based on the accuracies calculated, we concluded that the signatures used in the color invariants method produce the best re- sults, since they are parts-based signatures or signatures which take spacial information into account. The dominant colors and color histograms methods do not work very well, since they are holistic approaches. Usually, the color histograms approach gives better results than the dominant colors approach, however, dominant colors can work better in a situa- tion where the illumination changes are not much and consistent dominant colors can be obtained to describe a person or team. , like in the soccer dataset. Person re-identification based on appearance is a challenging problem, which works better if the clothes worn by the different people to be re-identified are very different in color and/or texture. In future, it would be interesting to see if superpixels can be used to divide the person into meaningful parts which can then be matched for person re-identification. Finally, the reports ends with acknowledgement and a synopsis of my personal experience.
author2 Qian Kemao
author_facet Qian Kemao
Chikersal, Prerna
format Industrial Attachment (IA)
author Chikersal, Prerna
author_sort Chikersal, Prerna
title Person re-identification using appearance
title_short Person re-identification using appearance
title_full Person re-identification using appearance
title_fullStr Person re-identification using appearance
title_full_unstemmed Person re-identification using appearance
title_sort person re-identification using appearance
publishDate 2014
url http://hdl.handle.net/10356/61790
_version_ 1759853924006756352