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
3D-2D projective registration of free-form curves and surfaces
Computer Vision and Image Understanding
Globally Consistent Range Scan Alignment for Environment Mapping
Autonomous Robots
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Learning hierarchical object maps of non-stationary environments with mobile robots
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Recovering articulated object models from 3D range data
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
SCAPE: shape completion and animation of people
ACM SIGGRAPH 2005 Papers
Global non-rigid alignment of 3-D scans
ACM SIGGRAPH 2007 papers
Reconstruction of deforming geometry from time-varying point clouds
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
International Journal of Computer Vision
Topology-Invariant Similarity of Nonrigid Shapes
International Journal of Computer Vision
Global correspondence optimization for non-rigid registration of depth scans
SGP '08 Proceedings of the Symposium on Geometry Processing
Automatic registration for articulated shapes
SGP '08 Proceedings of the Symposium on Geometry Processing
Automatic 3d free form shape matching using the graduated assignment algorithm
Pattern Recognition
Animation cartography—intrinsic reconstruction of shape and motion
ACM Transactions on Graphics (TOG)
Motion estimation for 3d rigid object shapes based on 3d-2d color-consistency in multi-view
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
An efficient human model customization method based on orthogonal-view monocular photos
Computer-Aided Design
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The iterative closest point (ICP) algorithm [2] is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models [5; 16; 9], this paper presents an ICP algorithm capable of modeling nonrigid objects, where individual scans may be subject to local deformations. We describe an integrated mathematical framework for simultaneously registering scans and recovering the surface configuration. To tackle the resulting high-dimensional optimization problems, we introduce a hierarchical method that first matches a coarse skeleton of scan points, then adapts local scan patches. The approach is implemented for a mobile robot capable of acquiring 3D models of objects.