Object Reconstruction and Recognition leveraging an RGB-D Camera

Recently, sensing devices capable of delivering realtime color and depth information have become available. We show how they can benefit to 3D object model acquisition, detection and pose estimation in the context of robotic manipulation. On the modeling side, we propose a volume carving algorithm capable of reconstructing rough 3D shape with a low processing cost. On the detection side, we find that little robustness can be directly added to classical feature-based techniques, but we propose an interesting combination with traditionally less robust techniques such as histogram comparison. We finally observe that 3D pose estimates can also be greatly improved using the depth measurements.