Sciweavers

Share
IBPRIA
2007
Springer

Motion Segmentation from Feature Trajectories with Missing Data

9 years 7 months ago
Motion Segmentation from Feature Trajectories with Missing Data
Abstract. This paper presents a novel approach for motion segmentation from feature trajectories with missing data. It consists of two stages. In the first stage, missing data are filled in by applying a factorization technique to the matrix of trajectories. Since the number of objects in the scene is not given and the rank of this matrix can not be directly computed, a simple technique for matrix rank estimation, based on a frequency spectra representation, is proposed. In the second stage, motion segmentation is obtained by using a clustering approach based on the normalized cuts criterion. Finally, the shape S and motion M of each of the obtained clusters (i.e., single objects) are recovered by applying classical SFM techniques. Experiments with synthetic and real data are provided in order to demonstrate the viability of the proposed approach.
Carme Julià, Angel Domingo Sappa, Felipe Lu
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where IBPRIA
Authors Carme Julià, Angel Domingo Sappa, Felipe Lumbreras, Joan Serrat, Antonio M. López
Comments (0)
books