An approach is described that integrates multiple visual sensing methodologies that yield three-dimensional information. The current system integrates feature-based stereo algorithms with various shape-from-texture algorithms. Unlike most systems for multisensor integration, that fuse all the information at one conceptual level, e.g., the surface level, the system under development uses two levels of data fusion: intraprocess integration and interprocess integration. Intraprocess integration techniques for feature-based stereo and shape-from-texture algorithms are briefly discussed. The authors also discuss an interprocess integration technique for fusing feature-based stereo and shape-from-texture based on smooth models of surfaces. Examples are presented using camera-acquired images.>

This paper describes an approach to the classification and segmentation of textured imagery. The approach utilizes information derived during the recovery of surface shape parameters, which are generated by a system that integrates multiple shape-from cues. The robustness of this approach is illustrated by a system that integrates several shape-from-texture cues, recovering not only shape information but also segmenting images into surfaces and aiding in the classification of the surface textures. Two examples are given of the system operating on real, camera acquired imagery.