This paper describes a full 6D localization algorithm based on probabilistic motion field. The motion field is obtained by an adaptation of the video compression algorithm known as Block-Matching which provides a sparse optical flow. Such a technique is very fast and allows real time applications. Image is decomposed in a grid of rectangular blocks. For each block, a relative displacement between consecutive images is calculated. Obtained motion flow is analyzed probabilistically in order to extract for each movement detection its uncertainty and to obtain subpixelic information about the area movement. Such motion flow is then used in order to obtain full 6 degrees of freedom camera localization using epipolar geometry based techniques without any 3D landmark reconstruction requirement. The method is applied to real data set obtained from a mobile robot and compared with SIFT and Harris detection.