Mobile landmark recognition

Significant advances have been made in the field of computer vision, in particular Mobile Visual Search and the recognition of objects and places virtually through the development of feature detectors and descriptors. This project compares the performance of three key point detectors, Difference-of-...

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Main Author: Eyu, Zhi Wei
Other Authors: Yap Kim Hui
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/61267
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-612672023-07-07T17:29:45Z Mobile landmark recognition Eyu, Zhi Wei Yap Kim Hui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Significant advances have been made in the field of computer vision, in particular Mobile Visual Search and the recognition of objects and places virtually through the development of feature detectors and descriptors. This project compares the performance of three key point detectors, Difference-of-Gaussians (DoG), Harris-Affine and Hessian-Affine detectors, based on repeatability, in the presence of image transformations, such as changes in viewpoint angle, scale, image blur, JPEG compression and illumination. The two more common matching algorithms, Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF), are also compared in terms of matching and recognising the same scene using the same image data set. The experiment has found the Hessian-Affine detector and SURF to have the best performance. Bachelor of Engineering 2014-06-06T07:47:53Z 2014-06-06T07:47:53Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61267 en Nanyang Technological University 62 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::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Eyu, Zhi Wei
Mobile landmark recognition
description Significant advances have been made in the field of computer vision, in particular Mobile Visual Search and the recognition of objects and places virtually through the development of feature detectors and descriptors. This project compares the performance of three key point detectors, Difference-of-Gaussians (DoG), Harris-Affine and Hessian-Affine detectors, based on repeatability, in the presence of image transformations, such as changes in viewpoint angle, scale, image blur, JPEG compression and illumination. The two more common matching algorithms, Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF), are also compared in terms of matching and recognising the same scene using the same image data set. The experiment has found the Hessian-Affine detector and SURF to have the best performance.
author2 Yap Kim Hui
author_facet Yap Kim Hui
Eyu, Zhi Wei
format Final Year Project
author Eyu, Zhi Wei
author_sort Eyu, Zhi Wei
title Mobile landmark recognition
title_short Mobile landmark recognition
title_full Mobile landmark recognition
title_fullStr Mobile landmark recognition
title_full_unstemmed Mobile landmark recognition
title_sort mobile landmark recognition
publishDate 2014
url http://hdl.handle.net/10356/61267
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