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An efficient neuromorphic analog network for motion estimation

机译:用于运动估计的有效神经形态模拟网络

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Optical flow estimation is a critical mechanism for autonomous mobile robots as it provides a range of useful information. As real-time processing is mandatory in this case, an efficient solution is the use of specific very large scale integration (VLSI) analog circuits. This paper presents a simple and regular architecture based on analog circuits, which implements the entire processing line from photoreceptor to accurate and reliable optical flow estimation. The algorithm we propose, is an energy-based method using a novel wideband velocity-tuned filter which proves to be an efficient alternative to the well-known Gabor filters. Our approach shows that a high level of accuracy can be obtained from a small number of loosely tuned filters. It exhibits similar or improved performance to that of other existing algorithms, but with a much lower complexity
机译:光流估计是自主移动机器人的关键机制,因为它提供了一系列有用的信息。由于在这种情况下必须进行实时处理,因此有效的解决方案是使用特定的超大规模集成电路(VLSI)模拟电路。本文提出了一种基于模拟电路的简单而规则的体系结构,该体系结构实现了从感光器到准确而可靠的光流估计的整个处理线。我们提出的算法是一种使用新型宽带速度调谐滤波器的基于能量的方法,该方法被证明是众所周知的Gabor滤波器的有效替代方案。我们的方法表明,可以从少量松散调整的滤波器中获得较高的准确性。它表现出与其他现有算法相似或更高的性能,但复杂度低得多

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