Title
Motion representation using composite energy features
Abstract
This work tackles the segmentation of apparent-motion from a bottom-up perspective. When no information is available to build prior high-level models, the only alternative are bottom-up techniques. Hence, the whole segmentation process relies on the suitability of the low-level features selected to describe motion. A wide variety of low-level spatio-temporal features have been proposed so far. However, all of them suffer from diverse drawbacks. Here, we propose the use of composite energy features in bottom-up motion segmentation to solve several of these problems. Composite energy features are clusters of energy filters-pairs of band-pass filters in quadrature-each one sensitive to a different set of scale, orientation, direction of motion and speed. They are grouped in order to reconstruct independent motion patterns in a video sequence. A composite energy feature, this is, the response of one of these clusters of filters, can be built as a combination of the responses of the individual filters. Therefore, it inherits the desirable properties of energy filters but providing a more complete representation of motion patterns. In this paper, we will present our approach for integration of composite features based on the concept of Phase Congruence. We will show some results that illustrate the capabilities of this low-level motion representation and its usefulness in bottom-up motion segmentation and tracking.
Year
DOI
Venue
2008
10.1016/j.patcog.2007.07.021
Pattern Recognition
Keywords
DocType
Volume
bottom-up perspective,low-level motion representation,bottom-up motion segmentation,composite energy feature,energy filter,motion pattern,energy filters-pairs,independent motion pattern,composite feature,bottom-up technique,band pass filter,signal processing,difference set,image segmentation,feature selection,motion estimation,image processing,bottom up,image reconstruction
Journal
41
Issue
ISSN
Citations 
3
Pattern Recognition
4
PageRank 
References 
Authors
0.44
25
3
Name
Order
Citations
PageRank
Raquel Dosil114510.37
Xosé R. Fdez-Vidal2935.87
Xose Manuel Pardo312613.25