Possibility theory and rough histograms for motion estimation in a video sequence

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2059, Issue , 2001, Pages 473-483

  Comby, Frederic ^a   Strauss, Olivier ^a   Aldon, Marie José ^a  

^a LIRMM   (France)

Author keywords

[No Author keywords available]

Indexed keywords

GRAPHIC METHODS; OPTICAL CORRELATION; VIDEO RECORDING;

ESTIMATION METHODS; FLOW-BASED METHODS; FUZZY MODELING; POSSIBILITY THEORY; THEORETICAL ASPECTS; VIDEO SEQUENCES;

MOTION ESTIMATION;

EID: 84957547875     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45129-3_43     Document Type: Conference Paper

References (7)

1. B. K. P. Horn and B. G. Schunck. Determining optical flow. Artificial Intelligence, 17: 185-203, 1981.
2. J. M. Odobez and P. Bouthemy. Robust multi-resolution estimation of parametric motion models applied to complex scenes. Pi 788, IRISA, 1994.
3. D. Dubois and H. Prade. Possibility Theory An Approach to Computerized Processing of Uncertainty. Plenum Press, 1988.
4. D. Dubois, H. Prade, and C. Testemale. Weighted fuzzy pattern matching. Fuzzy sets and systems, 28: 313-331, May 1988.
5. O. Strauss, F. Comby, and M. J. Aldon. Rough histograms for robust statistics. In International Conference on Pattern Recognition, volume 2, pages 688-691. IAPR, September 2000.
6. P. Smets and R. Kennes. The transferable belief model. Artificial Intelligence, 66: 191-243, 1994.
7. T. Denoeux. Reasoning with imprecise belief structures. Technical Report 97/44, Universite de Technologie de Compiegne, Heudiasyc Laboratory, 1997.