The motion estimation techniques used by the video compression standards provide an efficient utilization of the transmission and storage resources, through the reduction of the number of bits required to represent a video signal and the conservation of the content quality that is being processed. The objective of this work is to propose a new algorithm capable of reducing the great computational complexity involved in the motion estimation techniques, keeping the quality of the reconstructed signal. In this way, we present an algorithm called AUMHS (Adaptive Unsymmetrical-cross Multi-Hexagon-grid Search) which brings as main modifications relative to the UMHS (Unsymmetrical-cross Multi-Hexagon-grid Search) the implementation of a movement measure that can classify the scenes of a video sequence according to the motion detected for posterior adequacy of the motion estimation and others coder parameters. As result we present an expressive gain in the processing speed, and consequent computational cost reduction, conserving the same quality of the main algorithms published in the literature. The algorithm was implemented in the H.264/AVC coder in order to proceed with comparative analysis of perfomance together with the UMHS and FSA algorithms, measuring parameters as PSNR (Peak Signal you the Noise Ratio), coding processing time, motion estimation time, bit rate, and informal subjective evaluation.