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Page 123 Table 2.11, m=1: Replace "YK=K1 (X0 cos(Z0)+Y0sin(Z0))" with "YK=K1 (Y0 cos(Z0)+X0sin(Z0))" Page 123 Table 2.11, m=-1: Replace "XK=K-1√X0 2 + Y0 2 " with "XK=K-1√X0 2-Y0 2 " Replace "YK=K-1 (X0 cosh(Z0)+Y0sinh(Z0))" with "YK=K-1 (Y0 cosh(Z0)+X0sinh(Z0)

Page 123 Table 2.11, m=1: Replace "YK=K1 (X0 cos(Z0)+Y0sin(Z0))" with "YK=K1 (Y0 cos(Z0)+X0sin(Z0))" Page 123 Table 2.11, m=-1: Replace "XK=K-1√X0 2 + Y0 2 " with "XK=K-1√X0 2-Y0 2 " Replace "YK=K-1 (X0 cosh(Z0)+Y0sinh(Z0))" with "YK=K-1 (Y0 cosh(Z0)+X0sinh(Z0)

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Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integration (VLSI) technology. These algorithms, as well as the hardware implementation, are presented here together with an extensive analysis of the resources needed and the throughput obtained. The developed low-cost system is practical for real-time throughput and reduced power consumption and is useful in robotic applications, such as tracking, navigation using an unmanned vehicle, or as part of a more complex system.