Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Model-based recognition in robot vision
ACM Computing Surveys (CSUR)
Object recognition using oriented model points
Computer Vision, Graphics, and Image Processing
Polyhedra recognition by hypothesis accumulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms in combinatorial geometry
Algorithms in combinatorial geometry
Object recognition and localization via pose clustering
Computer Vision, Graphics, and Image Processing
A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Pose Determination of a Three-Dimensional Object Using Triangle Pairs
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Sensitivity of the Hough Transform for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Recognizing solid objects by alignment with an image
International Journal of Computer Vision
Exact and Approximate Solutions of the Perspective-Three-Point Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polynomial-time geometric matching for object recognition
Polynomial-time geometric matching for object recognition
A study of affine matching with bounded sensor error
International Journal of Computer Vision
3-D Pose from 3 Points Using Weak-Perspective
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polynomial-Time Object Recognition in the Presence of Clutter, Occlusion, and Uncertainty
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Measuring the Quality of Hypotheses in Model-Based Recognition
ECCV '92 Proceedings of the Second European Conference on Computer Vision
On the speed and accuracy of object recognition when using imperfect grouping
ISCV '95 Proceedings of the International Symposium on Computer Vision
Robust Affine Structure Matching for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A General Method for Geometric Feature Matching and Model Extraction
International Journal of Computer Vision
SoftPOSIT: Simultaneous Pose and Correspondence Determination
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A General Method for Feature Matching and Model Extraction
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
SoftPOSIT: Simultaneous Pose and Correspondence Determination
International Journal of Computer Vision
Efficient partial-surface registration for 3D objects
Computer Vision and Image Understanding
Probabilistic matching and resemblance evaluation of shapes in trademark images
Proceedings of the 6th ACM international conference on Image and video retrieval
Efficient partial-surface registration for 3D objects
Computer Vision and Image Understanding
Analyzing DGI-BS: properties and performance under occlusion and noise
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Pose sampling for efficient model-based recognition
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Combining geometric and appearance priors for robust homography estimation
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data
International Journal of Computer Vision
3D scene retrieval and recognition with Depth Gradient Images
Pattern Recognition Letters
The MOPED framework: Object recognition and pose estimation for manipulation
International Journal of Robotics Research
An efficient approximation algorithm for point pattern matching under noise
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
Improved Algorithms for Matching r-Separated Sets with Applications to Protein Structure Alignment
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Pose clustering is a method to perform object recognition bydetermining hypothetical object poses and finding clusters of theposes in the space of legal object positions. An object that appearsin an image will yield a large cluster of such poses close to thecorrect position of the object. If there are m model features and n image features, then there are O(m^3n^3) hypothetical posesthat can be determined from minimal information for the case ofrecognition of three-dimensional objects from feature points intwo-dimensional images. Rather than clustering all of these poses,we show that pose clustering can have equivalent performance for thiscase when examining only O(mn) poses, due to correlation between the poses, if we are given two correct matches between model features and image features. Since we do not usually know two correct matchesin advance, this property is used with randomization to decompose thepose clustering problem into O(n^2) problems, each of whichclusters O(mn) poses, for a total complexity of O(mn^3). Furtherspeedup can be achieved through the use of grouping techniques. Thismethod also requires little memory and makes the use of accurateclustering algorithms less costly. We use recursive histogramingtechniques to perform clustering in time and space that is guaranteedto be linear in the number of poses. Finally, we present resultsdemonstrating the recognition of objects in the presence of noise,clutter, and occlusion.