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Dependable 3D perception modules are essential for safe operation of autonomous systems. Therefore, we present a highly compact stereo vision system that gets along without a dedicated processing platform, having the DSPs integrated in the cameras. To enable the computation of dense and accurate depth maps, we implement a Sparse Census Transform, reducing the complexity of the stereo matching procedure...
Stereo vision has become a very interesting sensing technology for robotic platforms. It offers various advantages, but the drawback is a very high algorithmic effort. Due to the aptitude of certain non-parametric techniques for field programmable gate array (FPGA) based stereo matching, these algorithms can be implemented in highly parallel design while offering adequate real-time behavior. To enable...
This paper presents the hardware implementation of a stereo vision core algorithm, that runs in real-time and is targeted at automotive applications. The algorithm is based on the sum of absolute differences (SAD) and computes the disparity map using 320 times 240 input images with a maximum disparity of 100 pixels. The hardware operates at a frequency of 65 MHz and achieves a frame rate of 425 fps...
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