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This paper presents a method of 3D localization using image edge-points detected from binocular stereo image sequences. The proposed method calculates camera poses using visual odometry, and updates the poses by reducing the accumulated errors using landmark recognition. Landmark recognition is done based on robust and scalable image-retrieval using image edge-points with SIFT descriptors and a vocabulary tree. A randomized-ICP algorithm is employed to accurately estimate the 6-DOF camera pose from a landmark image and an edge-point based 3D map. Experiments show our edge-point based approach outperforms approaches using corners and Laplacian points.