TY - GEN
T1 - Parallel distributed detection of feature trajectories in multiple discontinuous motion image sequences
AU - Thirumalai, Srikanth
AU - Ahuja, Narendra
PY - 1993
Y1 - 1993
N2 - This paper is concerned with three-dimensional interpretation of image sequences showing multiple objects in motion. Each object is assumed to have point features which are detected automatically, and exhibits smooth motion except at times when a motion discontinuity may occur. The problem of estimating initial feature trajectories is that of matching between the first two frames. As more images are acquired, existing trajectories are extended. Both initial detection and extension are formulated as energy minimization problems that are solved using a Hopfield network. The energy function incorporates pertinent 2-D and 3-D geometric constraints. A second, 1-D Hopfield-like network is used to eliminate wrong matches among those found by the first network.
AB - This paper is concerned with three-dimensional interpretation of image sequences showing multiple objects in motion. Each object is assumed to have point features which are detected automatically, and exhibits smooth motion except at times when a motion discontinuity may occur. The problem of estimating initial feature trajectories is that of matching between the first two frames. As more images are acquired, existing trajectories are extended. Both initial detection and extension are formulated as energy minimization problems that are solved using a Hopfield network. The energy function incorporates pertinent 2-D and 3-D geometric constraints. A second, 1-D Hopfield-like network is used to eliminate wrong matches among those found by the first network.
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M3 - Conference contribution
AN - SCOPUS:0027837843
SN - 0780314212
SN - 9780780314214
T3 - Proceedings of the International Joint Conference on Neural Networks
SP - 2069
EP - 2072
BT - Proceedings of the International Joint Conference on Neural Networks
PB - Publ by IEEE
T2 - Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
Y2 - 25 October 1993 through 29 October 1993
ER -