A Moving Object Detection Algorithm Based on Color Information

This paper designed a new algorithm of moving object detection for the aim of quick moving object detection and orientation, which used a pixel and its neighbors as an image vector to represent that pixel and modeled different chrominance component pixel as a mixture of Gaussians, and set up differe...

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Vydáno v:Journal of physics. Conference series Ročník 48; číslo 1; s. 384 - 387
Hlavní autoři: Fang, X H, Xiong, W, Hu, B J, Wang, L T
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.10.2006
Témata:
Algorithms
Color
Image segmentation
Moving object recognition
Physics
Pixels
Spatial data
ISSN:1742-6596, 1742-6588, 1742-6596
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Abstract This paper designed a new algorithm of moving object detection for the aim of quick moving object detection and orientation, which used a pixel and its neighbors as an image vector to represent that pixel and modeled different chrominance component pixel as a mixture of Gaussians, and set up different mixture model of Gauss for different YUV chrominance components. In order to make full use of the spatial information, color segmentation and background model were combined. Simulation results show that the algorithm can detect intact moving objects even when the foreground has low contrast with background.
AbstractList This paper designed a new algorithm of moving object detection for the aim of quick moving object detection and orientation, which used a pixel and its neighbors as an image vector to represent that pixel and modeled different chrominance component pixel as a mixture of Gaussians, and set up different mixture model of Gauss for different YUV chrominance components. In order to make full use of the spatial information, color segmentation and background model were combined. Simulation results show that the algorithm can detect intact moving objects even when the foreground has low contrast with background.
Author Hu, B J
Xiong, W
Wang, L T
Fang, X H
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CitedBy_id crossref_primary_10_1109_TPAMI_2017_2717828
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crossref_primary_10_1016_j_cosrev_2018_01_004
crossref_primary_10_1016_j_sigpro_2015_10_011
crossref_primary_10_21307_ijssis_2017_934
crossref_primary_10_1109_JSEN_2016_2574989
Cites_doi 10.1109/34.868683
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SubjectTerms Algorithms
Color
Image segmentation
Moving object recognition
Physics
Pixels
Spatial data
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