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Real-time Semi-Global Matching on the CPU

Stefan K. Gehrig, Clemens Rabe
Group Research & Advanced Engineering, Daimler AG, HPC 059-G024, 71059 Sindelfingen, Germany
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2010

@inproceedings{gehrig2010real,

   title={Real-Time Semi-Global Matching on the CPU},

   author={Gehrig, S.K. and Rabe, C.},

   booktitle={Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on},

   pages={85–92},

   year={2010},

   organization={IEEE}

}

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Among the top-performing stereo algorithms on the Middlebury Stereo Database, Semi-Global Matching (SGM) is commonly regarded as the most efficient algorithm. Consequently, real-time implementations of the algorithm for graphics hardware (GPU) and reconfigurable hardware (FPGA) exist. However, the computation time on general purpose PCs is still more than a second. In this paper, a real-time SGM implementation on a general purpose PC is introduced. Parallelization and image subsampling is used while ensuring the full disparity resolution for small disparities. This approach is especially beneficial for robotic and driver assistance systems. The system is able to compute 640×320 image pairs at more than 14Hz, leaving also computational resources for subsequent processing such as free space computation or object detection. The algorithmic approach is portable to multi-core embedded processors.
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