Parallel distributed detection of feature trajectories in multiple discontinuous motion image sequences

Srikanth Thirumalai, Narendra Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherPubl by IEEE
Pages2069-2072
Number of pages4
ISBN (Print)0780314212, 9780780314214
StatePublished - 1993
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
Duration: Oct 25 1993Oct 29 1993

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume3

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period10/25/9310/29/93

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Parallel distributed detection of feature trajectories in multiple discontinuous motion image sequences'. Together they form a unique fingerprint.

Cite this