CISE Experimental Partnerships: High Performance Systems for Shape and Action Modeling

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99-01249Davis, Larry SUniversity of MarylandCISE Experimental Partnerships: High Performance Systems for Shape andAction ModelingResearch is being performed on the design and development of parallel algorithms for obtaining accurate models of natural objects and actions. The goal of the work is to develop a suite of parallel, distributed algorithms executing on a network of personal computers that can integrate video images from multiple viewpoints to construct an accurate geometric model of a complex, rigid object, or detailed dynamic action models of moving, articulated and non-rigid objects - specifically people. The work integrates and extends previous research in computer vision, hierarchical data structures and high performance software systems. Geometric and statistical algorithms for extracting shape and action descriptions from single and multiple video streams are being used along with hierarchical spatial data structures (e.g. oct-trees and quadtrees) which constitute the basic data structures for the shape and action representations being constructed. The enormous quantity of data and computation associated with applying such techniques and structures to a large number of video streams makes it impossible for vision scientists alone to design, construct and evaluate the omputational performance of these distributed algorithms and systems. Vision researchers are working together with parallel and distributed computing researchers to articulate a solution that includes geometric, algorithmic, and systems-oriented perspectives.