Combination of multiple features for object/background segmentation using graph cut

Jisuanji Yanjiu yu Fazhan/Computer Research and Development

Volumn 45, Issue 10, 2008, Pages 1724-1730

  Deng, Yu ^a,b   Li, Hua ^a,b  

^a INSTITUTE OF COMPUTING TECHNOLOGY   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Color; Gradient; Graph cut; Moving objects segmentation; Multiple feature combination; Texture

Indexed keywords

COMPUTER APPLICATIONS; COMPUTER VISION; DETECTOR CIRCUITS; IMAGE PROCESSING; MATHEMATICAL MORPHOLOGY; TEXTURES;

BACKGROUND MODELS; COMPUTER VISION APPLICATIONS; FOREGROUND OBJECTS; FUNDAMENTAL PROBLEMS; GRADIENT; GRAPH CUT; GRAPH CUT ALGORITHMS; GRAPH CUTS; ILLUMINATION CHANGES; LINEAR COMBINATIONS; MORPHOLOGICAL OPERATIONS; MOVING OBJECTS; MOVING OBJECTS SEGMENTATION; MULTIPLE FEATURE COMBINATION; MULTIPLE FEATURES; NATURAL SCENES; NOVEL METHODS; OBJECTS SEGMENTATIONS; REAL SCENES; TEXTURE FEATURES;

GRAPH THEORY;

EID: 55949108814     PISSN: 10001239     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Wren C, Azarbayejani A, Darrell T, et al. Pfinder: Real-time tracking of the human body[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19(7): 780-785
2. Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking[C]//Proc of IEEE Conf on Computer Vision and Pattern Recognition. Los Alamitos: IEEE Computer Society, 1999
3. 4: Real-time surveillance of people and their activities[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2000, 22(8): 809-830
4. Kato J, Watanabe T, Joga S, et al. An HMM-based segmentation method for traffic monitoring movies[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2002, 24(9): 1291-1296
5. Elgammal A, Harwood D, Davis L S. Non-parametric model for background subtraction[C]//Proc of the 6th European Conf on Computer Vision. New York: Springer, 2000
6. Monnet A, Mittal A, Paragios N, et al. Background modeling and subtraction of dynamics scenes[C]//Proc of IEEE Int Conf on Computer Vision. Los Alamitos: IEEE Computer Society, 2003
7. Horprasert T, Harwood D, Davis L S. A statistical approach for real-time robust background subtraction and shadow detection[C]//Proc of IEEE ICCV 1999 FRAME-RATE Workshop. Los Alamitos: IEEE Computer Society, 1999
8. Thongkamwitoon T, Aramvith S, Chalidabhongse T H. An adaptive real-time background subtraction and moving shadows detection[C]//Proc of IEEE Int Conf on Multimedia and Expo. Los Alamitos: IEEE Computer Society, 2004
9. Jabri J S, Duric Z, Wechsler H, et al. Detection and location of people in video images using adaptive fusion of color and edge information[C]//Proc of Int Conf on Pattern Recognition. Los Alamitos: IEEE Computer Society, 2000
10. Chen Rui, Deng Yu, Xiang Shiming, et al. A non-parametric foreground/background segmentation method by fusion of intensity and edge feature[J]. Journal of Computer-Aided Design and Computer Graphics, 2005, 17(6): 1278-1284 (in Chinese)
11. Xiang Shiming, Chen Rui, Deng Yu, et al. Motion segmentation via on-line Gaussian mixture model and texture[J]. Journal of Computer-Aided Design and Computer Graphics, 2005, 17(7): 1504-1509 (in Chinese)
12. Mi Congjie, Liu Yang, Xue Xiangyang. Video texts tracking and segmentation based on multiple frames[J]. Journal of Computer Research and Development, 2006, 43(9): 1523-1529 (in Chinese)
13. Boykov Y, Kolmogorov V. An experimental comparison of min-cut/max-flow algorithm for energy minimization in vision[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2004, 26(9): 1124-1137
14. Freedman D, Zhang T. Interactive graph cut based segmentation with shape priors[C]//Proc of IEEE Int Conf on Computer Vision and Pattern Recognition. Los Alamitos: IEEE Computer Society, 2005
15. Kohli P, Torr P H S. Efficiently solving dynamic Markov random fields using graph cuts[C]//Proc of IEEE Int Conf on Computer Vision. Los Alamitos: IEEE Computer Society, 2005
16. Ojala T, Pietikainen M, Maenpaa T. Multiresolution grayscale and rotation invariant texture classification with local binary pattern[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987