Object Tracking Using Low Level Image Features

碩士 === 國立中正大學 === 電機工程研究所 === 105 === Object tracking is an important research field in computer vision in that it continuously identifies and records objects of interest in video frames. This thesis attempts to do object tracking using only low-level image features. The basic idea is to employ the...

Full description

Bibliographic Details
Main Authors: Kuan-Wei Chen, 陳冠維
Other Authors: Ching-Wei Yeh
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/452wn6
id ndltd-TW-105CCU00442012
record_format oai_dc
spelling ndltd-TW-105CCU004420122019-05-15T23:09:04Z http://ndltd.ncl.edu.tw/handle/452wn6 Object Tracking Using Low Level Image Features 以影像基礎特徵進行物件追蹤 Kuan-Wei Chen 陳冠維 碩士 國立中正大學 電機工程研究所 105 Object tracking is an important research field in computer vision in that it continuously identifies and records objects of interest in video frames. This thesis attempts to do object tracking using only low-level image features. The basic idea is to employ the low-level features to compose the so-called singular points, and to use these singular points as the basis for matching the object of interest in adjacent image frames. We demonstrate that if the tracking region surrounding the object of interest is well defined and maintained, the proposed method can provide effective tracking even under the conditions of minor obscurity, deformation, and re-entry. Ching-Wei Yeh 葉經緯 2016 學位論文 ; thesis 58 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立中正大學 === 電機工程研究所 === 105 === Object tracking is an important research field in computer vision in that it continuously identifies and records objects of interest in video frames. This thesis attempts to do object tracking using only low-level image features. The basic idea is to employ the low-level features to compose the so-called singular points, and to use these singular points as the basis for matching the object of interest in adjacent image frames. We demonstrate that if the tracking region surrounding the object of interest is well defined and maintained, the proposed method can provide effective tracking even under the conditions of minor obscurity, deformation, and re-entry.
author2 Ching-Wei Yeh
author_facet Ching-Wei Yeh
Kuan-Wei Chen
陳冠維
author Kuan-Wei Chen
陳冠維
spellingShingle Kuan-Wei Chen
陳冠維
Object Tracking Using Low Level Image Features
author_sort Kuan-Wei Chen
title Object Tracking Using Low Level Image Features
title_short Object Tracking Using Low Level Image Features
title_full Object Tracking Using Low Level Image Features
title_fullStr Object Tracking Using Low Level Image Features
title_full_unstemmed Object Tracking Using Low Level Image Features
title_sort object tracking using low level image features
publishDate 2016
url http://ndltd.ncl.edu.tw/handle/452wn6
work_keys_str_mv AT kuanweichen objecttrackingusinglowlevelimagefeatures
AT chénguānwéi objecttrackingusinglowlevelimagefeatures
AT kuanweichen yǐyǐngxiàngjīchǔtèzhēngjìnxíngwùjiànzhuīzōng
AT chénguānwéi yǐyǐngxiàngjīchǔtèzhēngjìnxíngwùjiànzhuīzōng
_version_ 1719140885708406784