A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Multidimensional binary search trees used for associative searching
Communications of the ACM
ICP Registration Using Invariant Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model Based Pose Estimation for Autonomous Operations in Space
ICIIS '99 Proceedings of the 1999 International Conference on Information Intelligence and Systems
Fast and accurate shape-based registration
Fast and accurate shape-based registration
Near-optimal selection of views and surface regions for ICP pose estimation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
CSCA-based expectivity indices for LIDAR computer vision
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
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This paper proposes a method to select a near-optimal laser scanning area on a target body that will result in the best registration accuracy. The method is based on constraint analysis and employs a sensitivity index which is used as a registration accuracy predictor. It is shown that point cloud configurations with higher values of this index return more accurate pose estimates than unstable configurations with lower index values. Iterative Closest Point (ICP) registration tests are conducted on four satellite geometries using synthetic range data. The proposed method can be used to increase the accuracy of ICP registration and to reduce registration processing time.