Triangulation based technique for efficient stereo computation in infrared images

This paper proposes a technique to compute an accurate semi-dense disparity map from infrared stereo image pairs obtained using an uncalibrated stereo rig. First, an initial sparse disparity map is obtained using corner matching methods. This map is then refined using our proposed triangular constraints and the epipolar geometrical constraints to yield a more accurate semidense disparity map. Experimental results obtained using the proposed method are reported along with results obtained with a classical correlation based method as well as a more recent method based on graph-cuts. The proposed method yields good results even with low resolution, low texture infrared images. The proposed method is designed to be part of a vision-based occupant sensing system that will help to control airbag deployment in future vehicles.