DocumentCode :
3054272
Title :
Autonomous motion vision
Author :
Taalebinezhaad, M. Ali
Author_Institution :
MIT, Artificial Intelligence Lab., Cambridge, MA, USA
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
232
Lastpage :
235
Abstract :
Earlier, the author (1991) introduced a direct method called fixation for the recovery of shape and motion in the general case. The method uses neither feature correspondence nor optical flow. Instead, it directly employs the spatio-temporal gradients of images brightnesses. The present paper reports the experimental results of applying some of the fixation algorithms to a sequence of real images where the motion is a combination of translation and rotation. Techniques for autonomous choice of parameters which result in good estimates for important motion parameters are also described
Keywords :
computer vision; image sequences; parameter estimation; autonomous motion vision; computer vision; fixation algorithms; images brightnesses; motion parameter estimation; pattern recognition; real image sequences; shape recovery; spatio-temporal gradients; Artificial intelligence; Brightness; Cameras; Computer vision; Equations; Laboratories; Motion estimation; Optical computing; Shape; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2910-X
Type :
conf
DOI :
10.1109/ICPR.1992.201548
Filename :
201548
Link To Document :
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