Matching and retrieval of motion sequences has become an important research area in recent years, due to the increasing availability and popularity of motion capture data. The main challenge in matching two motion sequences is the diversity of the captured motions, including variable length, local shifting, local and global scaling. Most existing methods employ Dynamic Time Warping (DTW) or Uniform Scaling to handle these problems. In this paper, we propose a novel content-based method for matching of this human motion captured data. We convert the matching problem of motion capture data into a transportation problem. To solve this problem efficiently, we employ Earth Mover's Distance (EMD) as the matching framework. To penalize any strayed matching, we provide a ground distance that works similar to SakoeChiba band of DTW. Empirical results obtained are encouraging.