Abstract
Signal processing algorithms often have to be modified significantly for implementation in hardware. Continuous real-time image processing at high speed is a particularly challenging task. In this paper a hardware-software codesign is applied to a stereophotogrammetric system. To calculate the depth map, an optimized algorithm is implemented as a hierarchical-parallel hardware solution. By subdividing distances to objects and selecting them sequentially, we can apply 3D scanning and ranging over large distances. We designed processor-based object clustering and tracking functions. We can detect objects utilizing density distributions of disparities in the depth map (disparity histogram). Motion parameters of detected objects are stabilized by Kalman filters.
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