DocumentCode :
889548
Title :
The accuracy of the computation of optical flow and of the recovery of motion parameters
Author :
Micheli, E.D. ; Torre, Vincent ; Uras, Sergio
Author_Institution :
Istituto di Cibernetica e Biofisica, CNR, Genova, Italy
Volume :
15
Issue :
5
fYear :
1993
fDate :
5/1/1993 12:00:00 AM
Firstpage :
434
Lastpage :
447
Abstract :
The accuracy and the dependence on parameters of a general scheme for the analysis of time-varying image sequences are discussed. The approach is able to produce vector fields from which it is possible to recover 3-D motion parameters such as time-to-collision and angular velocity. The numerical stability of the computed optical flow and the dependence of the recovery of 3-D motion parameters on spatial and temporal filtering is investigated. By considering optical flows computed on subsampled images or along single scanlines, it is also possible to recover 3-D motion parameters from reduced optical flows. An adequate estimate of time-to-collision can be obtained from sequences of images with spatial resolution reduced to 128×128 pixels or from sequences of single scanlines passing near the focus of expansion. The use of Kalman filtering increases the accuracy and the robustness of the estimation of motion parameters. The proposed approach seems to be able to provide not only a theoretical background but also practical tools that are adequate for the analysis of time-varying image sequences
Keywords :
filtering and prediction theory; image sequences; motion estimation; optical information processing; parameter estimation; 128 pixels; 16384 pixels; 3D motion parameter recovery; Kalman filtering; angular velocity; optical flow; scanlines; spatial filtering; subsampled images; temporal filtering; time-to-collision; time-varying image sequences; Angular velocity; Filtering; Image analysis; Image motion analysis; Image sequence analysis; Image sequences; Numerical stability; Optical computing; Optical filters; Spatial resolution;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.211464
Filename :
211464
Link To Document :
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