A CAM enabled fast video motion estimation based on locality sensitive signatures
Pavel Arnaudov, Tokunbo Ogunfunmi · 2017
Motion estimation consumes the major part of time and power in both video compression standards - HEVC and H.264. This paper presents a Fast Motion Estimation algorithm, which targets Full Search quality even at HD resolution. It is an enhancement of existing Fast Motion Estimation algorithms with the main purpose of reducing cost and power consumption for devices performing Motion Estimation while collecting and transmitting video data (used for deep learning). The proposed algorithm is based on dimensionality reduction and uses Content Addressable Memories (CAMs) and locality sensitive signatures to achieve “Quantitative Expression of Similarity”. The algorithm also presents an enhancement to one of the most efficient existing Fast Motion Estimation algorithms for lower resolutions - HMDS. The quality achieved with the new algorithm is only 3dB below Full Search.