A Dual Source, Parallel Architecture for Computer Vision

摘要

We present a parallel architecture for object recognition and location based on concurrent processing of depth and intensity image data. Parallel algorithms for curvature computation and segmentation of depth data into planar or curved surface patches, and edge detection and segmentation of intensity data into extended linear features, are described. Using this feature data in comparison with a CAD model, objects can be located in either depth or intensity images by a parallel pose clustering algorithm.