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Robust foreground extraction technique using Gaussian Family model and multiple thresholds

Robust foreground extraction technique using Gaussian Family model and multiple thresholds
Robust foreground extraction technique using Gaussian Family model and multiple thresholds
We propose a robust method to extract silhouettes of foreground objects from color video sequences. To cope with various changes in the background, the background is modeled as generalized Gaussian Family of distributions and updated by the selective running average and static pixel observation. All pixels in the input video image are classified into four initial regions using background subtraction with multiple thresholds, after which shadow regions are eliminated using color components. The final foreground silhouette is extracted by refining the initial region using morphological processes. We have verified that the proposed algorithm works very well in various background and foreground situations through experiments.
Background subtraction, Foreground segmentation, Generalized Gaussian Family model, Silhouette extraction, Algorithms, Color vision, Gaussian distribution, Pixels, Color video sequences, Gaussian Family model, Feature extraction
0302-9743
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Sakamoto, R.
6cdb329c-4cb0-42d6-b4b0-68b448304398
Kitahara, I.
13b48c1f-8b52-4b65-9f98-e00c2bee22df
Toriyama, T.
060a3980-f003-4b15-b0fb-7e9e99acc471
Kogure, K.
9862d198-bf93-48a3-a954-dd8bce232b8b
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Sakamoto, R.
6cdb329c-4cb0-42d6-b4b0-68b448304398
Kitahara, I.
13b48c1f-8b52-4b65-9f98-e00c2bee22df
Toriyama, T.
060a3980-f003-4b15-b0fb-7e9e99acc471
Kogure, K.
9862d198-bf93-48a3-a954-dd8bce232b8b

Kim, H., Sakamoto, R., Kitahara, I., Toriyama, T. and Kogure, K. (2007) Robust foreground extraction technique using Gaussian Family model and multiple thresholds (Lecture Notes in Computer Science, , (doi:10.1007/978-3-540-76386-4_72), 4843), vol. 4843, 11pp.

Record type: Book

Abstract

We propose a robust method to extract silhouettes of foreground objects from color video sequences. To cope with various changes in the background, the background is modeled as generalized Gaussian Family of distributions and updated by the selective running average and static pixel observation. All pixels in the input video image are classified into four initial regions using background subtraction with multiple thresholds, after which shadow regions are eliminated using color components. The final foreground silhouette is extracted by refining the initial region using morphological processes. We have verified that the proposed algorithm works very well in various background and foreground situations through experiments.

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More information

Published date: 2007
Additional Information: Cited By :27 Export Date: 30 April 2020
Keywords: Background subtraction, Foreground segmentation, Generalized Gaussian Family model, Silhouette extraction, Algorithms, Color vision, Gaussian distribution, Pixels, Color video sequences, Gaussian Family model, Feature extraction

Identifiers

Local EPrints ID: 440549
URI: http://eprints.soton.ac.uk/id/eprint/440549
ISSN: 0302-9743
PURE UUID: 25d55466-522f-42f9-9e8f-6682e7ca065a
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

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Date deposited: 07 May 2020 16:31
Last modified: 23 May 2020 00:47

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