This paper presents a new sensor system, CALOS, for motion estimation and 3D reconstruction. The
2D laser sensor provides accurate depth information of a plane, not the whole 3D structure. On the contrary, the
CCD cameras provide the projected image of whole 3D scene, not the depth of the scene. To overcome the
limitations, we combine these two types of sensors, the laser sensor and the CCD cameras. We develop a motion
estimation scheme appropriate for this sensor system. In the proposed scheme, the motion between two frames is
estimated by using three points among the scan data and their corresponding image points, and refined by
non-linear optimization. We validate the accuracy of the proposed method by 3D reconstruction using real
images. The results show that the proposed system can be a practical solution for motion estimation as well as
for 3D reconstruction.
2D laser sensor provides accurate depth information of a plane, not the whole 3D structure. On the contrary, the
CCD cameras provide the projected image of whole 3D scene, not the depth of the scene. To overcome the
limitations, we combine these two types of sensors, the laser sensor and the CCD cameras. We develop a motion
estimation scheme appropriate for this sensor system. In the proposed scheme, the motion between two frames is
estimated by using three points among the scan data and their corresponding image points, and refined by
non-linear optimization. We validate the accuracy of the proposed method by 3D reconstruction using real
images. The results show that the proposed system can be a practical solution for motion estimation as well as
for 3D reconstruction.