实时量化光流

Ted Camus
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引用次数: 111

摘要

基于图像斑块相关性的算法在实践中具有鲁棒性,但由于其基于搜索的计算复杂性,计算量很大。随着时间而不是空间执行搜索本质上是线性的,而不是二次的,并且会产生非常有效的算法。这与在标准计算硬件上高效的实现相结合,在科学工作站上产生每秒超过5帧的性能。虽然结果速度是量化的结果量化误差,他们已经被证明是足够准确的许多机器人视觉任务,如碰撞时间和机器人导航。因此,该算法非常适合实时机器人视觉研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time quantized optical flow
Algorithms based on the correlation of image patches can be robust in practice but are computationally intensive due to the computational complexity of their search-based nature. Performing the search over time instead of over space is linear in nature, rather than quadratic, and results in a very efficient algorithm. This, combined with implementations which are highly efficient on standard computing hardware, yields performance of over 5 frames per second on a scientific workstation. Although the resulting velocities are quantized with resulting quantization error, they have been shown to be sufficiently accurate for many robotic vision tasks such as time-to-collision and robotic navigation. Thus, this algorithm is highly suitable for real-time robotic vision research.
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