A GPU-based implementation of motion detection from a moving platform

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops

Volumn , Issue , 2008, Pages

  Yu, Qian ^a   Medioni, Gérard ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKGROUND MODELING; CAMERA MOTIONS; MOTION DETECTION; MOTION FIELDS; MOVING CAMERAS; MOVING PLATFORMS; REGISTRATION ERRORS; SLIDING WINDOWS;

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; ERROR ANALYSIS; FEATURE EXTRACTION; IMAGE PROCESSING; PATTERN RECOGNITION; STANDARDS;

CAMERAS;

EID: 51849123304     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2008.4563096     Document Type: Conference Paper

References (17)

1. http://developer.nvidia.com/object/cg_toolkit.html.
2. J. Shi and C. Tomas. Good features to track. In CVPR, pages 593-600, 1994.
3. P. Babenko and M. Shah. Mingpu: A minimum gpu library for computer vision. http://server.cs.ucf.edu/vision/MinGPU/.
4. C. A. James Fung, Steve Mann. Openvidia: Parallel gpu computer vision. In Proceedings of the ACM Multimedia 2005, pages 849-852, 2005.
5. R. J. Radke et al. Image change detection algorithms: A systematic survey. IEEE Transactions on Image Processing, pages 294-307, 2005.
6. A. Griesser et al. Real-time, gpu-based foreground-background segmentation. In Vision, Modeling, and Visualization, pages 319-326, 2005.
7. R. K. Patrick Labatut and J.-P. Pons. A gpu implementation of level set multiview stereo. In International Conference on Computational Science, pages 212-219, 2006.
8. C. Stauffer and W. Grimson. Adaptive background mixture models for real-time tracking. In CVPR, pages 246-252, 1999.
9. J. Kang, I. Cohen, and G. Medioni. Continuous tracking within and across camera streams. In CVPR, volume 1, pages 267-272, Jun 2003.
10. R. Yang and M. Pollefeys. Multi-resolution real-time stereo on commodity graphics hardware. In CVPR, pages 211-217, 2003.
11. S. N. Sinha, J.-M. Frahm, M. Pollefeys, and Y. Genc. Gpubased video feature tracking and matching. Technical report, Department of Computer Science, UNC Chapel Hill, 2006.
12. S. Mann and R. W. Picard. Video orbits of the projective group a simple approach to featureless estimation of parameters. IEEE Transactions on Image Processing, pages 1281-1295, 1997.
13. R. Mester, T. Aach, and L. Dumbgen. Illumination-invariant change detection using a statistical colinearity criterion. In Proc. 23rd DAGM Symp, pages 170-177, 2001.
14. Z. Yin and R. Collins. Belief propagation in a 3d spatiotemporal mrf for moving object detection. In CVPR, 2007.
15. C. Yuan, G. Medioni, J. Kang, and I. Cohen. Detecting motion regions in presence of strong parallax from a moving camera by multi-view geometric constraints. In PAMI, volume 29, pages 1627-1641, 2007.
16. M. Fisher and R. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. In Comm. Assoc. Comp., volume 24(6), pages 381-39, 1981.
17. J. Kruger and R. Westermann. Linear algebra operators for gpu implementation of numerical algorithms. In International Conference on Computer Graphics and Interactive Techniques, 2003.