Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Model-based recognition in robot vision
ACM Computing Surveys (CSUR)
The representation, recognition, and locating of 3-d objects
International Journal of Robotics Research
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing solid objects by alignment with an image
International Journal of Computer Vision
A new curve tracing algorithm and some applications
Curves and surfaces
On the Verification of Hypothesized Matches in Model-Based Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stability and likelihood of views of three dimensional objects
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Sensor Modeling, Probabilistic Hypothesis Generation, and Robust Localization for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Review and analysis of solutions of the three point perspective pose estimation problem
International Journal of Computer Vision
Let them fall where they may: capture regions of curved objects and polyhedra
International Journal of Robotics Research
Computer Vision and Image Understanding
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
View Variation of Point-Set and Line-Segment Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Pose from 3 Points Using Weak-Perspective
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Indexing for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical learning, localization, and identification of objects
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Locating objects using the Hausdorff distance
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
An Unified Approach to Model-Based and Model-Free Visual Servoing
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
3D target recognition using cooperative feature map binding under Markov Chain Monte Carlo
Pattern Recognition Letters
Object recognition using point uncertainty regions as pose uncertainty regions
Image and Vision Computing
Probabilistic 3D object recognition based on multiple interpretations generation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Dependable 3D object recognition with two-layered particle filter
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
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A probabilistic 3D object recognition algorithm is presented.In order to guide the recognition process theprobability that match hypotheses between image features and modelfeatures are correct is computed. A model is developed whichuses the probabilistic peaking effect of measured angles andratios of lengths by tracing iso-angle and iso-ratio curves onthe viewing sphere. The model also accounts for various typesof uncertainty in the input such as incomplete and inexact edge detection.For each match hypothesis the pose of the object and thepose uncertainty which is due to the uncertainty in vertexposition are recovered. This is used to find sets of hypotheseswhich reinforce each other by matching features of the sameobject with compatible uncertainty regions. A probabilisticexpression is used to rank these hypothesis sets.The hypothesis sets with the highest rank are output.The algorithm has been fully implemented, and tested on real images.