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Graph-based foreground extraction in extended color space

Graph-based foreground extraction in extended color space
Graph-based foreground extraction in extended color space
We propose a region-based method to extract semantic foreground regions from color video sequences with static backgrounds. First, we introduce a new distance measure for background subtraction which is robust against shadows. Then the foreground region is extracted with a graph-based region segmentation method considering background difference and spatial homogeneity. For efficient computation, the graph structure is optimized by the minimum spanning tree before segmentation. The main contribution is that the proposed algorithm improves on conventional approaches especially in strong shadow regions and does not require manual initialization. We have verified through experiments and comparison to state of the art methods that the proposed algorithm works well with various cameras and environment. ©2009 IEEE.
Background subtraction, Graph algorithm, Minimum spanning tree, Clustering algorithms, Color, Image segmentation, Imaging systems, Parallel architectures, Video recording, Color space, Color video, Conventional approach, Distance measure, Efficient computation, Foreground extraction, Foreground regions, Graph algorithms, Graph structures, Graph-based, Minimum spanning trees, Region segmentation, Region-based methods, Shadow regions, Spatial homogeneity, State-of-the-art methods, Static background, Trees (mathematics)
3221-3224
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db

Kim, H. and Hilton, Adrian (2009) Graph-based foreground extraction in extended color space. 16th IEEE International Conference on Image Processing, Egypt. 07 - 10 Nov 2009. pp. 3221-3224 . (doi:10.1109/ICIP.2009.5414370).

Record type: Conference or Workshop Item (Paper)

Abstract

We propose a region-based method to extract semantic foreground regions from color video sequences with static backgrounds. First, we introduce a new distance measure for background subtraction which is robust against shadows. Then the foreground region is extracted with a graph-based region segmentation method considering background difference and spatial homogeneity. For efficient computation, the graph structure is optimized by the minimum spanning tree before segmentation. The main contribution is that the proposed algorithm improves on conventional approaches especially in strong shadow regions and does not require manual initialization. We have verified through experiments and comparison to state of the art methods that the proposed algorithm works well with various cameras and environment. ©2009 IEEE.

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More information

e-pub ahead of print date: 7 November 2009
Venue - Dates: 16th IEEE International Conference on Image Processing, Egypt, 2009-11-07 - 2009-11-10
Keywords: Background subtraction, Graph algorithm, Minimum spanning tree, Clustering algorithms, Color, Image segmentation, Imaging systems, Parallel architectures, Video recording, Color space, Color video, Conventional approach, Distance measure, Efficient computation, Foreground extraction, Foreground regions, Graph algorithms, Graph structures, Graph-based, Minimum spanning trees, Region segmentation, Region-based methods, Shadow regions, Spatial homogeneity, State-of-the-art methods, Static background, Trees (mathematics)

Identifiers

Local EPrints ID: 440570
URI: http://eprints.soton.ac.uk/id/eprint/440570
PURE UUID: 51216b81-70b2-4384-b7da-3b2c1d4e36cf
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

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Date deposited: 07 May 2020 16:37
Last modified: 07 Oct 2020 02:27

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Contributors

Author: H. Kim ORCID iD
Author: Adrian Hilton

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