Multi-view gait-based human identification with automatic joint detection

This research work proposes a joint detection approach to detect locations of body joint automatically by applying a priori knowledge of body proportion. The joint detection approach does not attempt to detect each lower limb of a human, so it can detect the body joints even from self-occluded silho...

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Main Author: Ng, Hu
Format: Thesis
Published: 2014
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id my-mmu-ep.5989
record_format uketd_dc
spelling my-mmu-ep.59892023-04-12T07:56:15Z Multi-view gait-based human identification with automatic joint detection 2014-01 Ng, Hu TK7800-8360 Electronics This research work proposes a joint detection approach to detect locations of body joint automatically by applying a priori knowledge of body proportion. The joint detection approach does not attempt to detect each lower limb of a human, so it can detect the body joints even from self-occluded silhouettes or those occluded by apparel (long blouses or baggy trousers) or bags (handbag or rucksack). In this research work, an improved perspective correction technique to normalize oblique-view walking sequences to side-view plane has been developed. The silhouettes from oblique-view walking sequences are vertical and horizontal adjusted to fit the sideview. 2014-01 Thesis http://shdl.mmu.edu.my/5989/ http://erep.mmu.edu.my/ phd doctoral Multimedia University Faculty of Computing and Informatics EREP ID: 7948
institution Multimedia University
collection MMU Institutional Repository
topic TK7800-8360 Electronics
spellingShingle TK7800-8360 Electronics
Ng, Hu
Multi-view gait-based human identification with automatic joint detection
description This research work proposes a joint detection approach to detect locations of body joint automatically by applying a priori knowledge of body proportion. The joint detection approach does not attempt to detect each lower limb of a human, so it can detect the body joints even from self-occluded silhouettes or those occluded by apparel (long blouses or baggy trousers) or bags (handbag or rucksack). In this research work, an improved perspective correction technique to normalize oblique-view walking sequences to side-view plane has been developed. The silhouettes from oblique-view walking sequences are vertical and horizontal adjusted to fit the sideview.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Ng, Hu
author_facet Ng, Hu
author_sort Ng, Hu
title Multi-view gait-based human identification with automatic joint detection
title_short Multi-view gait-based human identification with automatic joint detection
title_full Multi-view gait-based human identification with automatic joint detection
title_fullStr Multi-view gait-based human identification with automatic joint detection
title_full_unstemmed Multi-view gait-based human identification with automatic joint detection
title_sort multi-view gait-based human identification with automatic joint detection
granting_institution Multimedia University
granting_department Faculty of Computing and Informatics
publishDate 2014
_version_ 1776101413940625408