Motion Estimation of objects between consecutive video frames pose a unique challenge due to the difficulty to implement standard motion estimation techniques in this case, given the lack of distinctive features and the great difference between the frames. In this project we developed a system which, given 2 consecutive video frames, matches large objects between them and estimates the translation transformation from one frame to another, while dealing with occlusions. The algorithm consists of 4 main steps. First, Region Merging segmentation is performed. Then, large segments identified in both frames are matched using EMD algorithm. Next, segmentation is improved by merging segments, using the matching results between the frames. Last, motion estimation of large segments is done using incremental search of segment from one frame within the matching region in the other frame. This is done while dealing with occlusions by removing artificial edges created due to the occlusion. The system successfully estimates translation transformations of large objects in synthetic images as well as in natural images while dealing with occlusions.