Paper Info
Title
Spatio-temporal shape building from image sequences using lateral interaction in accumulative computation
Abstract
To be able to understand the motion of non-rigid objects, techniques in image processing and computer vision are essential for motion analysis. Lateral interaction in accumulative computation for extracting non-rigid shapes from an image sequence has recently been presented, as well as its application to segmentation from motion. In this paper, we introduce a modified version of the first multi-layer architecture. This version uses the basic parameters of the LIAC model to spatio-temporally build up to the desired extent the shapes of all moving objects present in a sequence of images. The influences of LIAC model parameters are explained in this paper, and we finally show some examples of the usefulness of the model proposed.
Year
DOI
Venue
2003
10.1016/S0031-3203(02)00116-4
Pattern Recognition
Keywords
Field
DocType
Segmentation from motion,Image analysis,Shape representation,Silhouette recognition,Lateral interaction,Accumulative computation
Computer vision,Motion field,Pattern recognition,Segmentation,Computer science,Image processing,Artificial intelligence,Motion analysis,Image sequence,Machine learning,Computation
Journal
Volume
Issue
ISSN
36
5
0031-3203
Citations 
PageRank 
References 
35
1.66
11
Authors
4
Name
Order
Citations
PageRank
Antonio Fernandez-Caballero1818.74
Miguel A. Fernandez2965.93
Jose Mira3684.92
Ana E. Delgado424316.85