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Motion Vision

Description

This comprehensive book deals with motion estimation for autonomous systems from a biological, algorithmic and digital perspective. An algorithm, which is based on the optical flow constraint equation, is described in detail. This algorithm fits with the motion processing model, hardware and software constraints and resolves depth-velocity ambiguity, which is critical for autonomous navigation. There is also extensive coverage on the use of this algorithm in digital hardware, and the initial motion processing model, the chosen hardware platforms, and the global function of the system are all described. Essential for those interested in intelligent control, automation, autonomous systems and automotive engineering, and machine vision systems.

Keywords

motion sensing solutions dynamic scale space least absolute residuals estimator neighbouring estimates ground plane motion smooth ground plane inhibit flag implicit synchronisation rigid body motion model brightness constancy assumption selected signal assignment buffer schematic camera buffer tristate buffers truncated quadratic motion estimates scale equivariant motion estimation techniques range discontinuities std logic motion estimation algorithm localisation accuracy motion estimation problem optical flow estimates based motion estimation

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