A Trajectory-based Point Tracker Using Chaos Evolutionary Programming

碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 95 === A trajectory-based point tracker using chaos evolutionary programming (CEP) algorithm is proposed in this thesis. While motion constraints such as rigidity and small motion which are imposed by previous approaches are liberated, the proposed CEP is proved to b...

Full description

Bibliographic Details
Main Authors: Po-Nung Wu, 吳柏農
Other Authors: Shu-Mei Guo
Format: Others
Language:en_US
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/36842919067846783944
id ndltd-TW-095NCKU5392015
record_format oai_dc
spelling ndltd-TW-095NCKU53920152015-10-13T14:16:10Z http://ndltd.ncl.edu.tw/handle/36842919067846783944 A Trajectory-based Point Tracker Using Chaos Evolutionary Programming 基於渾沌進化演算論之有效影像軌跡為基礎的點追蹤器 Po-Nung Wu 吳柏農 碩士 國立成功大學 資訊工程學系碩博士班 95 A trajectory-based point tracker using chaos evolutionary programming (CEP) algorithm is proposed in this thesis. While motion constraints such as rigidity and small motion which are imposed by previous approaches are liberated, the proposed CEP is proved to be effective for establishing point correspondence between two consecutive frames sampled at a fixed interval. The whole point trajectory within the sample interval is then reconstructed by polynomial interpolation. Our experimental results demonstrate that the proposed point tracker can accurately locate target under different kinds of situations like object deformation, occlusion, and sudden motion as well. Shu-Mei Guo 郭淑美 2007 學位論文 ; thesis 60 en_US
collection NDLTD
language en_US
format Others
sources NDLTD
description 碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 95 === A trajectory-based point tracker using chaos evolutionary programming (CEP) algorithm is proposed in this thesis. While motion constraints such as rigidity and small motion which are imposed by previous approaches are liberated, the proposed CEP is proved to be effective for establishing point correspondence between two consecutive frames sampled at a fixed interval. The whole point trajectory within the sample interval is then reconstructed by polynomial interpolation. Our experimental results demonstrate that the proposed point tracker can accurately locate target under different kinds of situations like object deformation, occlusion, and sudden motion as well.
author2 Shu-Mei Guo
author_facet Shu-Mei Guo
Po-Nung Wu
吳柏農
author Po-Nung Wu
吳柏農
spellingShingle Po-Nung Wu
吳柏農
A Trajectory-based Point Tracker Using Chaos Evolutionary Programming
author_sort Po-Nung Wu
title A Trajectory-based Point Tracker Using Chaos Evolutionary Programming
title_short A Trajectory-based Point Tracker Using Chaos Evolutionary Programming
title_full A Trajectory-based Point Tracker Using Chaos Evolutionary Programming
title_fullStr A Trajectory-based Point Tracker Using Chaos Evolutionary Programming
title_full_unstemmed A Trajectory-based Point Tracker Using Chaos Evolutionary Programming
title_sort trajectory-based point tracker using chaos evolutionary programming
publishDate 2007
url http://ndltd.ncl.edu.tw/handle/36842919067846783944
work_keys_str_mv AT ponungwu atrajectorybasedpointtrackerusingchaosevolutionaryprogramming
AT wúbǎinóng atrajectorybasedpointtrackerusingchaosevolutionaryprogramming
AT ponungwu jīyúhúndùnjìnhuàyǎnsuànlùnzhīyǒuxiàoyǐngxiàngguǐjīwèijīchǔdediǎnzhuīzōngqì
AT wúbǎinóng jīyúhúndùnjìnhuàyǎnsuànlùnzhīyǒuxiàoyǐngxiàngguǐjīwèijīchǔdediǎnzhuīzōngqì
AT ponungwu trajectorybasedpointtrackerusingchaosevolutionaryprogramming
AT wúbǎinóng trajectorybasedpointtrackerusingchaosevolutionaryprogramming
_version_ 1717751148874563584