DocumentCode :
2658009
Title :
Moving target detection in image sequences
Author :
Tao, Zhang ; Shumin, Fei ; Xiaodong, Li ; Hong, Lu
Author_Institution :
Inst. of Autom., Southeast Univ., Nanjing
fYear :
2008
fDate :
16-18 July 2008
Firstpage :
445
Lastpage :
448
Abstract :
A novel and effective approach to the global motion estimation and moving object extraction is proposed in this paper. Firstly, the translational motion model was used by the fact that complex motion can be decomposed as a sum of translational components. Then in this application, the edge gray horizontal and vertical projections were used as the block matching feature for the motion vector estimation. The proposed algorithm reduces the motion estimation computations by calculating the one-dimensional vector rather than the two-dimensional ones. Once the global motion is robustly estimated, relatively stationary background can be almost completely eliminated through inter-frame difference method. To achieve an accurate object extraction result, the higher-order statistics (HOS) algorithm was used to discriminate background and moving object. Experiments have shown a robust result for global motion estimation and object extraction.
Keywords :
edge detection; feature extraction; higher order statistics; image sequences; motion estimation; object detection; block matching feature; edge gray horizontal projections; higher-order statistics algorithm; image sequences; inter-frame difference method; motion estimation computations; motion vector estimation; moving object extraction; moving target detection; translational components; translational motion model; vertical projections; Control systems; Hardware; Higher order statistics; Image sequences; Laboratories; Motion control; Motion estimation; Motion measurement; Object detection; Robustness; Edge Projection; Global Motion Estimation; HOS; Moving Object Extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
Type :
conf
DOI :
10.1109/CHICC.2008.4605031
Filename :
4605031
Link To Document :
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