Robust moving object detection and shadow removing based on improved gaussian model and gradient information

2010 International Conference on Multimedia Technology, ICMT 2010

Volumn , Issue , 2010, Pages

  Bin, Zhiyan ^a   Liu, Yunyi ^a  

^a GUANGXI UNIVERSITY   (China)

Author keywords

Gaussian mixture mode; Object detection; Self adaptive; Shadow removing

Indexed keywords

COLOR INFORMATION; COMPLEX SCENES; DETECTION RATES; EFFECTIVE ALGORITHMS; FIRST-ORDER; GAUSSIAN MIXTURE MODEL; GAUSSIAN MIXTURES; GAUSSIAN MODEL; GRADIENT INFORMATIONS; ILLUMINATION CHANGES; IMPROVED ALGORITHM; LEARNING RATES; MOVING OBJECTS; MOVING-OBJECT DETECTION; OBJECT DETECTION; SELF-ADAPTIVE; SHADOW REMOVING; VIDEO SURVEILLANCE;

ALGORITHMS; GAUSSIAN DISTRIBUTION; IMAGE SEGMENTATION; SECURITY SYSTEMS;

OBJECT RECOGNITION;

EID: 79952225799     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMULT.2010.5629797     Document Type: Conference Paper

References (13)

1. S.Fejes, L.S.Davis, "Detection of independent motion using directional motion estimation," Technical Report, CAR-TR-866, CS-TR 3815, University of Maryland, August 1997.
2. S.Fejes, L.S. Davis, "What can projections of flow fields tell us about the visual motion," ICCV'98, 4-7 January, Bombay, India.
3. S.Fejes, L.S.Davis, "Exploring visual motion using projections of flow fields," DARPA'97, 2-5 February, Virginia, USA.
4. L.Wixion, M.Hansen, "Detecting salient motion by accumulating directional-consistent flow," ICCV'9, 20-27 September, Greece.
5. N. Paragios, R. Deriche, "Geodesic active contours and level sets for the detection and tracking of moving objects," IEEE Transactions on Pattern Analysis and Machine Interface 22(3) :266-280, 2000.
6. P. Spagnolo, T.D'Orazio, M. Leo, and A. Distante, "Moving object segmentation by background subtraction and temporal analysis," Image and Vision Computing, 24, 411-423, 2006. (Pubitemid 43782941)
7. B. Shoushtarian, H.E.Bez, "A practical adaptive approach for dynamic background subtraction using an invariant colour model and object tracking," Pattern Recognition Letters, 26,5-26,2005.
8. Di Fan, Maoyong Cao, ChangZhi, and Changzhi Lv, "An updating method of self-adaptive background for moving objects detection in video," Audio, Language and Image Processing, ICALIP 2008 International Conference, 1497-1501, 2008.
9. C. Stauffer, W.E.L. Grimson, "Adaptive background mixture models for real-time tracking," Computer Vision and Pattern Recognition, 2(6):23-25, 1999.
10. R. Cucchiara, C. Grana, M. Piccardi and A. Prati, "Detecting moving objects, ghosts, and shadows in video streams," IEEE Trans. PAMI, 25(10):1337-1342, 2003.
11. A. Elgammal, R. Duraiswami, D .Harwood, and L. Davis, "Background and forground modeling using nonparametric kernel density estimation for visual surveillance," Proc. of the IEEE, 90(7):1151-1163, 2002.
12. Z. Zivkovic, and F .van der Heijden, "Efficient adaptive density estimation per image pixel for the task of background subtraction," Pattern Recognition Letters, vol .27(7): 773-780, 2006. (Pubitemid 43374860)
13. A. Monnet, Mittal, N. Paragios and V. Ramesh, "Background modeling and subtraction of dynamic scenes," Proceeding of the International Conference on Computer Vison, pp.1305-1312, 2003.