Title :
MRF-motion segmentation based on dominant motion estimation and the detection of uncovered regions
Author :
Silveira, Margarida ; Piedade, Moisés
Author_Institution :
INESC, Instituto Superior Tecnico, Lisbon, Portugal
fDate :
6/23/1905 12:00:00 AM
Abstract :
This paper presents an algorithm for the segmentation of multiple moving objects. Our proposal is based on dominant motion estimation, static segmentation and Markov random field (MRF) classification of the regions obtained by static segmentation. Dominant motion estimation is based on efficient variants of the Hough transform applied over a hierarchy of motion models with increasing complexity. The final segmentation is only performed after all the motion models have been determined and is based on motion information, which includes the explicit detection of uncovered regions and on contextual properties between neighboring static regions
Keywords :
Hough transforms; Markov processes; image classification; image segmentation; image sequences; motion estimation; object detection; Hough transform; Markov random field classification; contextual properties; dominant motion estimation; motion segmentation; multiple moving objects; static segmentation; uncovered region detection; Context modeling; Convergence; Markov random fields; Motion detection; Motion estimation; Motion segmentation; Object detection; Object segmentation; Proposals; Robustness;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.959031