Implementation of observation dependent visual object tracking using C++

Object tracking, an important task within the field of computer vision, is the problem of estimating the position and other relevant information of moving objects in image sequences. It is widely used in smart vision systems such as visual surveillance, visual navigation, human-computer interaction a...

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Main Author: Lu, Chengyuan
Other Authors: Lin Weisi
Format: Final Year Project
Language:English
Published: 2014
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Online Access:http://hdl.handle.net/10356/58945
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-589452023-03-03T20:49:19Z Implementation of observation dependent visual object tracking using C++ Lu, Chengyuan Lin Weisi School of Computer Engineering Centre for Multimedia and Network Technology DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Object tracking, an important task within the field of computer vision, is the problem of estimating the position and other relevant information of moving objects in image sequences. It is widely used in smart vision systems such as visual surveillance, visual navigation, human-computer interaction and video compression. Several kinds of object tracking algorithms have been implemented, most of which, however, are only adoptable for some specific target and environment. This project is about the implementation of visual object tracking algorithm based on the dependent Hidden Markov Model (ODHMM) framework where Structure Complexity Coefficient (SCC) models the observation dependency between consecutive frames. The main scope for this project is to convert the algorithm to the platform based on C++ from the MATLAB program, and the libraries such as OpenCV and Eigen are used in the project. Bachelor of Engineering (Computer Science) 2014-04-16T04:47:36Z 2014-04-16T04:47:36Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/58945 en Nanyang Technological University 43 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
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Lu, Chengyuan
Implementation of observation dependent visual object tracking using C++
description Object tracking, an important task within the field of computer vision, is the problem of estimating the position and other relevant information of moving objects in image sequences. It is widely used in smart vision systems such as visual surveillance, visual navigation, human-computer interaction and video compression. Several kinds of object tracking algorithms have been implemented, most of which, however, are only adoptable for some specific target and environment. This project is about the implementation of visual object tracking algorithm based on the dependent Hidden Markov Model (ODHMM) framework where Structure Complexity Coefficient (SCC) models the observation dependency between consecutive frames. The main scope for this project is to convert the algorithm to the platform based on C++ from the MATLAB program, and the libraries such as OpenCV and Eigen are used in the project.
author2 Lin Weisi
author_facet Lin Weisi
Lu, Chengyuan
format Final Year Project
author Lu, Chengyuan
author_sort Lu, Chengyuan
title Implementation of observation dependent visual object tracking using C++
title_short Implementation of observation dependent visual object tracking using C++
title_full Implementation of observation dependent visual object tracking using C++
title_fullStr Implementation of observation dependent visual object tracking using C++
title_full_unstemmed Implementation of observation dependent visual object tracking using C++
title_sort implementation of observation dependent visual object tracking using c++
publishDate 2014
url http://hdl.handle.net/10356/58945
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