Person re-identification for video surveillance

Person Re-Identification is a new technique compared to the person identification, which is more difficult and complex. It is easily affected by the surrounding environment and the person's gestures. Although Person Re-ID has made great progress in recent years, there are still a lot of problem...

Full description

Saved in:
Bibliographic Details
Main Author: Tang, Jinli
Other Authors: Chau Lap Pui
Format: Theses and Dissertations
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/72552
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-72552
record_format dspace
spelling sg-ntu-dr.10356-725522023-07-04T15:53:50Z Person re-identification for video surveillance Tang, Jinli Chau Lap Pui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Person Re-Identification is a new technique compared to the person identification, which is more difficult and complex. It is easily affected by the surrounding environment and the person's gestures. Although Person Re-ID has made great progress in recent years, there are still a lot of problems that need to be solved. In this thesis, the basic knowledge about person identification is introduced and reviewed. It then we introduced the image based Person Re-ID and video based Person Re-ID. For the theory and method, the TDL distance learning model was studied. Besides the TDL based method, the methods involving feature extration are also introduced. For the color feature, we used the localised average colour histogram. For the space-time feature, the HOG3d descriptor was used. Two datasets including iLIDS and PRID2011 were used for the experiment. Both experiments obtained good results: the Rank 1 rate for iLIDS is about 57% and the Rank 1 rate for PRID2011 is about 55%. They are better than the previous results, which lays the foundation for future work. Master of Science (Communications Engineering) 2017-08-28T11:35:34Z 2017-08-28T11:35:34Z 2017 Thesis http://hdl.handle.net/10356/72552 en 57 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::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Tang, Jinli
Person re-identification for video surveillance
description Person Re-Identification is a new technique compared to the person identification, which is more difficult and complex. It is easily affected by the surrounding environment and the person's gestures. Although Person Re-ID has made great progress in recent years, there are still a lot of problems that need to be solved. In this thesis, the basic knowledge about person identification is introduced and reviewed. It then we introduced the image based Person Re-ID and video based Person Re-ID. For the theory and method, the TDL distance learning model was studied. Besides the TDL based method, the methods involving feature extration are also introduced. For the color feature, we used the localised average colour histogram. For the space-time feature, the HOG3d descriptor was used. Two datasets including iLIDS and PRID2011 were used for the experiment. Both experiments obtained good results: the Rank 1 rate for iLIDS is about 57% and the Rank 1 rate for PRID2011 is about 55%. They are better than the previous results, which lays the foundation for future work.
author2 Chau Lap Pui
author_facet Chau Lap Pui
Tang, Jinli
format Theses and Dissertations
author Tang, Jinli
author_sort Tang, Jinli
title Person re-identification for video surveillance
title_short Person re-identification for video surveillance
title_full Person re-identification for video surveillance
title_fullStr Person re-identification for video surveillance
title_full_unstemmed Person re-identification for video surveillance
title_sort person re-identification for video surveillance
publishDate 2017
url http://hdl.handle.net/10356/72552
_version_ 1772825915565277184