The representation, recognition, and locating of 3-d objects
International Journal of Robotics Research
Structural Indexing: Efficient 3-D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
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
Optimal Registration of Object Views Using Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous registration of multiple range views for use in reverse engineering of CAD models
Computer Vision and Image Understanding - Special issue on CAD-based computer vision
ICP Registration Using Invariant Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Line Geometry
Special issue on registration and fusion of range images
Computer Vision and Image Understanding - Registration and fusion of range images
Surface registration by matching oriented points
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
A Fast Automatic Method for Registration of Partially-Overlapping Range Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Geometry and Convergence Analysis of Algorithms for Registration of 3D Shapes
International Journal of Computer Vision
Conformal Geometry and Its Applications on 3D Shape Matching, Recognition, and Stitching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving parabolic approximation of point clouds
Computer-Aided Design
Multiview registration for large data sets
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
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We propose a new model for simultaneous registration of multiple range views. The registration model minimizes a hybrid metric that is a combination of the tangent distance error and the sliding penalty. As a result, the proposed method is capable of reducing the sliding error in registration, especially for an object containing flat features. We used kinematical geometry to linearize rigid-body motions and approximate the registration model with a quadratic objective function, which leads to solving linear equations at each iteration. We also describe experiments indicating that our registration algorithm is insensitive to the initial alignment and maintains global stability.