Common pattern discovery using earth mover's distance and local flow maximization
In this paper, we present a novel segmentation-insensitive approach for mining common patterns from 2 images. We develop an algorithm using the earth movers distance (EMD) framework, unary and adaptive neighborhood color similarity. We then propose a novel local flow maximization approach to provide...
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sg-smu-ink.sis_research-73762021-11-23T02:46:57Z Common pattern discovery using earth mover's distance and local flow maximization TAN, Hung-Khoon NGO, Chong-wah In this paper, we present a novel segmentation-insensitive approach for mining common patterns from 2 images. We develop an algorithm using the earth movers distance (EMD) framework, unary and adaptive neighborhood color similarity. We then propose a novel local flow maximization approach to provide the best estimation of location and scale of the common pattern. This is achieved by performing an iterative optimization in search of the most stable flows' centroid. Common pattern discovery is difficult owing to the huge search space and problem domain. We intend to solve this problem by reducing the search space through identifying the location and a reduced spatial space for common pattern discovery. Experimental results justify the effectiveness and the potential of the approach. 2005-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6373 info:doi/10.1109/ICCV.2005.58 https://ink.library.smu.edu.sg/context/sis_research/article/7376/viewcontent/iccv05.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Graphics and Human Computer Interfaces |
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Computer Sciences Graphics and Human Computer Interfaces TAN, Hung-Khoon NGO, Chong-wah Common pattern discovery using earth mover's distance and local flow maximization |
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In this paper, we present a novel segmentation-insensitive approach for mining common patterns from 2 images. We develop an algorithm using the earth movers distance (EMD) framework, unary and adaptive neighborhood color similarity. We then propose a novel local flow maximization approach to provide the best estimation of location and scale of the common pattern. This is achieved by performing an iterative optimization in search of the most stable flows' centroid. Common pattern discovery is difficult owing to the huge search space and problem domain. We intend to solve this problem by reducing the search space through identifying the location and a reduced spatial space for common pattern discovery. Experimental results justify the effectiveness and the potential of the approach. |
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TAN, Hung-Khoon NGO, Chong-wah |
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TAN, Hung-Khoon NGO, Chong-wah |
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TAN, Hung-Khoon |
title |
Common pattern discovery using earth mover's distance and local flow maximization |
title_short |
Common pattern discovery using earth mover's distance and local flow maximization |
title_full |
Common pattern discovery using earth mover's distance and local flow maximization |
title_fullStr |
Common pattern discovery using earth mover's distance and local flow maximization |
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Common pattern discovery using earth mover's distance and local flow maximization |
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common pattern discovery using earth mover's distance and local flow maximization |
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Institutional Knowledge at Singapore Management University |
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2005 |
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https://ink.library.smu.edu.sg/sis_research/6373 https://ink.library.smu.edu.sg/context/sis_research/article/7376/viewcontent/iccv05.pdf |
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