DocumentCode :
3206436
Title :
Autonomous fixation
Author :
Taalebinezhaad, M. Ali
Author_Institution :
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
fYear :
1992
fDate :
15-18 Jun 1992
Firstpage :
744
Lastpage :
747
Abstract :
The author previously introduced a direct method, called fixation, for the recovery of shape and motion in the general case that uses neither feature correspondence nor optical flow. Instead, it directly uses the spatio-temporal gradients of image brightness. The experimental results of applying some of the author´s fixation algorithms to a sequence of real images, where the motion is a combination of translation and rotation, are reported. Techniques for autonomous choice of parameters that result in good estimates for important motion parameters are described
Keywords :
image sequences; motion estimation; fixation algorithms; image brightness; motion; motion parameters; real images; shape; spatio-temporal gradients; Artificial intelligence; Brightness; Computer vision; Equations; Image motion analysis; Laboratories; Motion estimation; Optical computing; Shape; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
Conference_Location :
Champaign, IL
ISSN :
1063-6919
Print_ISBN :
0-8186-2855-3
Type :
conf
DOI :
10.1109/CVPR.1992.223184
Filename :
223184
Link To Document :
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