Papers on Computer Vision
Methods for numerical integration of high-dimensional probability densities with application to statistical image models. S. M. LaValle, K. J. Moroney, and S. A. Hutchinson. IEEE Transactions on Image Processing, 6(12):1659-1672, December 1997. [pdf].
A framework for constructing probability distributions on the space of segmentations. S. M. LaValle and S. A. Hutchinson. Computer Vision and Image Understanding, 61(2):203-230, March 1995. [pdf].
A Bayesian segmentation methodology for parametric image models. S. M. LaValle and S. A. Hutchinson. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(2):211-218, February 1995. [pdf].
On considering uncertainty and alternatives in low-level vision. S. M. LaValle and S. A. Hutchinson. In Proceedings Ninth Conference on Uncertainty in Artificial Intelligence, pages 55-63, July 1993. [pdf].
Methods for numerical integration of high-dimensional probability densities with application to statistical image models. S. M. LaValle, K. J. Moroney, and S. A. Hutchinson. In Proceedings 1993 SPIE Conference on Neural and Stochastic Methods in Image and Signal Processing, pages 292-303, July 1993. [pdf].
Bayesian region merging probability for parametric image models. S. M. LaValle and S. A. Hutchinson. In Proceedings 1993 IEEE Conference on Computer Vision and Pattern Recognition, pages 778-779, June 1993. [pdf].
Agglomerative clustering on range data with a unified probabilistic merging function and termination criterion. S. M. LaValle, K. J. Moroney, and S. A. Hutchinson. In Proceedings 1993 IEEE Conference on Computer Vision and Pattern Recognition, pages 798-799, June 1993. [pdf].
A Bayesian framework for considering probability distributions of image segments and segmentations. S. M. LaValle. Master's thesis, University of Illinois, Urbana-Champaign, USA, December 1992. [pdf].