Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Registration and integration of textured 3-D data
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Heuristic-based laser scan matching for outdoor 6d SLAM
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
3D puppetry: a kinect-based interface for 3D animation
Proceedings of the 25th annual ACM symposium on User interface software and technology
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In this paper, we propose a system which reconstructs the environment with both color and 3D information. We perform extrinsic calibration of a camera and a LRF (Laser Range Finder) to fuse 3D information and color information of objects. We also formularize an equation to measure the result of the calibration. Moreover, we acquire 3D data by rotating 2D LRF with camera, and use ICP (Iterative Closest Point) algorithm to combine data acquired in other places. We use the SIFT (Scale Invariant Feature Transform) matching for the initial estimation of ICP algorithm. It offers accurate and stable initial estimation robust to motion change compare to odometry. We also modify the ICP algorithm using color information. Computation time of ICP algorithm can be reduced by using color information.