  This paper proposes a novel approach to stereo visual odometry without stereo
matching. It is particularly robust in scenes of repetitive high-frequency
textures. Referred to as DSVO (Direct Stereo Visual Odometry), it operates
directly on pixel intensities, without any explicit feature matching, and is
thus efficient and more accurate than the state-of-the-art
stereo-matching-based methods. It applies a semi-direct monocular visual
odometry running on one camera of the stereo pair, tracking the camera pose and
mapping the environment simultaneously; the other camera is used to optimize
the scale of monocular visual odometry. We evaluate DSVO in a number of
challenging scenes to evaluate its performance and present comparisons with the
state-of-the-art stereo visual odometry algorithms.
