Computational molecular biology
Computational molecular biology
A hierarchical approach to line extraction based on the Hough transform
Computer Vision, Graphics, and Image Processing
Model-based object recognition in dense-range images—a review
ACM Computing Surveys (CSUR)
An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric pattern matching under Euclidean motion
Computational Geometry: Theory and Applications - Special issue: computational geometry, theory and applications
Matching Sets of 3D Line Segments with Application to Polygonal Arc Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficiently Locating Objects Using the Hausdorff Distance
International Journal of Computer Vision
Approximate Geometric Pattern Matching Under Rigid Motions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
An optimal algorithm for approximate nearest neighbor searching
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Line-Based Recognition Using A Multidimensional Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Tabu Search
Reliable and Efficient Pattern Matching Using an Affine Invariant Metric
International Journal of Computer Vision
Matching 3-D Line Segments with Applications to Multiple-Object Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Pattern Matching in d-Dimensional Space
ESA '95 Proceedings of the Third Annual European Symposium on Algorithms
A geometric approach to the segmentation of range images
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Visibility-Based Test Scene Understanding by Real Plane Search
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Visibility-based modelling and control for network-based robotics
Pattern Recognition Letters
The Hausdorff fuzzy quasi-metric
Fuzzy Sets and Systems
Spatial Modelling for Mobile Robot's Vision-based Navigation
Journal of Intelligent and Robotic Systems
Hyperspaces of a weightable quasi-metric space: Application to models in the theory of computation
Mathematical and Computer Modelling: An International Journal
Robotics and Autonomous Systems
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Object recognition algorithms are fundamental tools in automatic matching of geometric shapes within a background scene. Many approaches have been proposed in the past to solve the object recognition problem. Two of the key aspects that distinguish them in terms of their practical usability are: (i) the type of input model description and (ii) the comparison criteria used. In this paper we introduce a novel scheme for 3D object recognition based on line segment representation of the input shapes and comparison using the Hausdorff distance. This choice of model representation provides the flexibility to apply the scheme in different application areas. We define several variants of the Hausdorff distance to compare the models within the framework of well-defined metric spaces. We present a matching algorithm that efficiently finds a pattern in a 3D scene. The algorithm approximates a minimization procedure of the Hausdorff distance. The output error due to the approximation is guaranteed to be within a known constant bound. Practical results are presented for two classes of objects: (i) polyhedral shapes extracted from segmented range images and (ii) secondary structures of large molecules. In both cases the use of our approximate algorithm allows to match correctly the pattern in the background while achieving the efficiency necessary for practical use of the scheme. In particular the performance is improved substantially with minor degradation of the quality of the matching.