Efficient sub-window search with fixed shape sub-windows

This paper addresses the performance improvement of efficient sub-window search algorithms for object detection. The current algorithms are for flexible rectangle-shaped sub-window with high computation costs. In this paper, a restriction is applied on the sub-window shape from rectangle into square...

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Bibliographic Details
Main Authors: Liang, Antoni, An, Senjian, Liu, Wan-Quan
Format: Journal Article
Published: Springer 2013
Online Access:http://hdl.handle.net/20.500.11937/18514
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author Liang, Antoni
An, Senjian
Liu, Wan-Quan
author_facet Liang, Antoni
An, Senjian
Liu, Wan-Quan
author_sort Liang, Antoni
building Curtin Institutional Repository
collection Online Access
description This paper addresses the performance improvement of efficient sub-window search algorithms for object detection. The current algorithms are for flexible rectangle-shaped sub-window with high computation costs. In this paper, a restriction is applied on the sub-window shape from rectangle into square in order to reduce the number of possible sub-windows with an expectation to improve the computation speed. However, this may come with a consequence of accuracy loss for some objects. In addition, another variance of sub-window shape is also tested which based on the ratio between the height and width of an image. The experiment results on the proposed algorithms were analysed and compared with the performance of the original algorithms to determine whether the speed improvement is significantly large while making the accuracy loss acceptable. It was found that some new algorithms show a good speed improvement while maintaining small accuracy loss. Furthermore, there is an algorithm designed from a combination of a new algorithm and an original algorithm which gains the benefit from both algorithms and produces the best performance among all new algorithms.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T07:26:08Z
publishDate 2013
publisher Springer
recordtype eprints
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spelling curtin-20.500.11937-185142017-09-13T13:43:51Z Efficient sub-window search with fixed shape sub-windows Liang, Antoni An, Senjian Liu, Wan-Quan This paper addresses the performance improvement of efficient sub-window search algorithms for object detection. The current algorithms are for flexible rectangle-shaped sub-window with high computation costs. In this paper, a restriction is applied on the sub-window shape from rectangle into square in order to reduce the number of possible sub-windows with an expectation to improve the computation speed. However, this may come with a consequence of accuracy loss for some objects. In addition, another variance of sub-window shape is also tested which based on the ratio between the height and width of an image. The experiment results on the proposed algorithms were analysed and compared with the performance of the original algorithms to determine whether the speed improvement is significantly large while making the accuracy loss acceptable. It was found that some new algorithms show a good speed improvement while maintaining small accuracy loss. Furthermore, there is an algorithm designed from a combination of a new algorithm and an original algorithm which gains the benefit from both algorithms and produces the best performance among all new algorithms. 2013 Journal Article http://hdl.handle.net/20.500.11937/18514 10.1007/s13042-012-0074-z Springer restricted
spellingShingle Liang, Antoni
An, Senjian
Liu, Wan-Quan
Efficient sub-window search with fixed shape sub-windows
title Efficient sub-window search with fixed shape sub-windows
title_full Efficient sub-window search with fixed shape sub-windows
title_fullStr Efficient sub-window search with fixed shape sub-windows
title_full_unstemmed Efficient sub-window search with fixed shape sub-windows
title_short Efficient sub-window search with fixed shape sub-windows
title_sort efficient sub-window search with fixed shape sub-windows
url http://hdl.handle.net/20.500.11937/18514