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
Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Registration and Integration of Multiple Object Views for 3D Model Construction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
ICP Registration Using Invariant Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Matching of 3-D curves using semi-differential invariants
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multi-Feature Matching Algorithm for Free-Form 3D Surface Registration
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Pseudo-linearizing collinearity constraint for accurate pose estimation from a single image
Pattern Recognition Letters
Metrological Analysis of a Procedure for the Automatic 3D Modeling of Dental Plaster Casts
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
3D Shape Registration using Regularized Medial Scaffolds
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Mechanism for Range Image Integration without Image Registration
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
3D Registration by Textured Spin-Images
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Pre-registration of arbitrarily oriented 3D surfaces using a genetic algorithm
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Fully Automatic Registration of 3D Point Clouds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Automatic 3d free form shape matching using the graduated assignment algorithm
Pattern Recognition
Multiview registration for large data sets
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Alignment of continuous video onto 3D point clouds
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Automatic 3D modeling of textured cultural heritage objects
IEEE Transactions on Image Processing
Constraints for closest point finding
Pattern Recognition Letters
Free form shape registration using the barrier method
Computer Vision and Image Understanding
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The SoftAssign algorithm is an elegant free form shape matching algorithm. While its objective function can be interpreted as consisting of three desired terms: minimising a weighted sum of matching errors of combinations of all the points in the two free form shapes to be matched, equalising their weights (probabilities) of being real ones and also maximising the overlapping area between the free form shapes to be matched, the last term has no effect on the optimisation of the parameters of interest due to normalisation. In this paper, we reformulate the last two terms using the inequality about the geometric and algebraic averages and the sum of the powers of these probabilities. For the sake of computational efficiency, instead of considering combinations of all the points in the overlapping free form shapes to be matched, we employ the traditional closest point criterion to establish possible correspondences between the two overlapping free form shapes to be matched. The saddle point solution of the resulting objective function no longer yields a closed form solution to the parameters of interest. For easy computation, we then adopt a pseudo-linearisation method to linearise the first order derivative of the objective function, leading the parameters of interest to be tracked and estimated with a closed form solution. The parameters of interest are finally optimised using the efficient deterministic annealing scheme with the camera motion parameters estimated using the quaternion method in the weighted least squares sense. A comparative study based on both synthetic data and real images with partial overlap has shown that the proposed algorithm is promising for the automatic matching of overlapping 3D free form shapes subject to a large range of motions.