The Factorization Method for Image Sequence Analysis

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This is the first year of a three-year continuing award. The long-term goal of this research is the recovery of accurate camera motion and dense three-dimensional shape information from television images at video rate. In prior work, the Principal Investigator developed a matrix-based factorization method for this task, based on a set of feature points tracked from frame to frame of a dense image sequence. Experiments with the method demonstrated a dramatic performance improvement over existing shape and motion recovery systems. This research will now develop a characterization of the noise sensitivity of image sequence analysis, explore efficient and incremental numerical methods for factorization, and reformulate the method for perspective projection, multiple motions, and dense shape results. As an exploratory advance into a new area of research an investigation of the link between motion analysis and multi- frame of object recognition will also be conducted. This research should contribute to a better theoretical understanding of visual motion analysis, and produce a vision module that would let a robot localize itself in the environment, draw a map of its own surroundings for navigation and obstacle avoidance, and perceive the shape of objects in order to recognize or manipulate them.