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Leveraging cost matrix structure for hardware implementation of stereo disparity computation using dynamic programming

机译：利用成本矩阵结构实现使用动态编程的立体视差计算的硬件实现

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摘要

Dynamic programming is a powerful method for solving energy minimisation problems in computer vision, for example stereo disparity computations. While it may be desirable to implement this algorithm in hardware to achieve frame-rate processing, a naive implementation may fail to meet timing require-ments. In this paper, the structure of the cost matrix is examined to provide improved methods of hard-ware implementation. It is noted that by computing cost matrix entries along anti-diagonals instead of rows, the cost matrix entries can be computed in a pipelined architecture. Further, if only a subset of the cost matrix needs to be considered, for example by placing limits on the disparity range (include neglecting negative disparities by assuming rectified images), the resources required to compute the cost matrix in parallel can be reduced. Boundary conditions required to allow computing a subset of the cost matrix are detailed. Finally, a hardware solution of Cox's maximum-likelihood, dynamic programming stereo disparity algorithm is implemented to demonstrate the performance achieved. The design pro-vides high frame rate (>123 fps) estimates for a large disparity range (e.g. 128 pixels), for image sizes of 640 x 480 pixels, and can be simply extended to work well over 200 fps.
机译：动态编程是解决计算机视觉中能量最小化问题（例如，立体视差计算）的一种强大方法。尽管可能需要在硬件中实现此算法以实现帧速率处理，但单纯的实现可能无法满足时序要求。本文研究了成本矩阵的结构，以提供改进的硬件实现方法。注意，通过沿着反对角线而不是行计算成本矩阵条目，可以在流水线体系结构中计算成本矩阵条目。此外，如果仅需要考虑成本矩阵的一个子集，例如通过对视差范围设置限制（包括通过假设校正图像来忽略负视差），则可以减少并行计算成本矩阵所需的资源。详细说明了允许计算成本矩阵子集所需的边界条件。最后，实现了Cox最大似然，动态编程立体声视差算法的硬件解决方案，以演示所实现的性能。该设计为640 x 480像素的图像尺寸提供了较大的视差范围（例如128像素）的高帧速率（> 123 fps）估计值，并且可以简单地扩展为在200 fps以上正常工作。

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