We summarize our recent work on a) a model based approach for estimation of kinematics and structure of a rigid object from a sequence of noisy images, b) extraction of edges and linear features from noise free and noisy real images using the directional derivatives estimated from a local non stationary random field model, and c) segmentation of textured images using Gauss Markov random field models and simulated annealing techniques. The research work summarized in this paper is supported in part by the NSF Grant DCI-84-51010, match-ing funds from IBM, AT&T, Hughes Aircraft Company, and TRW and by the Airforce Office of Scientific Research under the Contract F 49620-85-C-0071. The author acknowledges the contributions of T.J. Broida, S. Chatterjee, A. Rangarajan, T. Simchony, V. Venkateswar and Y. T. Zhou to the research results reported here.

Date Published: 6 June 1987
PDF: 13 pages
Proc. SPIE 0758, Image Understanding and the Man-Machine Interface, (6 June 1987); doi: 10.1117/12.940065

Published in SPIE Proceedings Vol. 0758:
Image Understanding and the Man-Machine Interface
Eamon B. Barrett; James J. Pearson, Editor(s)