Evidence-Based Recognition of 3-D Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic extraction of deformable part models
International Journal of Computer Vision
3-D vision techniques for autonomous vehicles
Analysis and interpretation of range images
The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Function-based generic recognition for multiple object categories
CVGIP: Image Understanding
Functional and physical object characteristics and object recognition in improvisation
Computer Vision and Image Understanding - Special issue of funtion-based vision
Recognition by functional parts
Computer Vision and Image Understanding - Special issue of funtion-based vision
Generic recognition of articulated objects through reasoning about potential function
Computer Vision and Image Understanding - Special issue of funtion-based vision
An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Physics-based visual understanding
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Communications of the ACM
Curves and surfaces for CAGD: a practical guide
Curves and surfaces for CAGD: a practical guide
Machine Learning
Generic Object Recognition: Building and Matching Coarse Descriptions from Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Comparison of Appearance and Geometric Model Based Recognition
ECCV '96 Proceedings of the International Workshop on Object Representation in Computer Vision II
Exploiting Context in Function-Based Reasoning
Revised Papers from the International Workshop on Sensor Based Intelligent Robots
A Framework for Representing Knowledge
A Framework for Representing Knowledge
Radial Basis Functions
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Using Interaction Signatures to Find and Label Chairs and Floors
IEEE Pervasive Computing
Generic Model Abstraction from Examples
IEEE Transactions on Pattern Analysis and Machine Intelligence
Creating Efficient Codebooks for Visual Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Tool use for autonomous agents
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Learning membership functions in a function-based object recognition system
Journal of Artificial Intelligence Research
FUR: Understanding functional reasoning
International Journal of Intelligent Systems
Model-Based Three-Dimensional Interpretations of Two-Dimensional Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foundations and Trends in Robotics
Object classification based on a geometric grammar with a range camera
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Robust sequence alignment for actor-object interaction recognition: Discovering actor-object states
Computer Vision and Image Understanding
Abstraction and generalization of 3D structure for recognition in large intra-class variation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Plane-based object categorisation using relational learning
Machine Learning
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We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical description of object classes is constructed. The object classes are described in terms of functional components. The multi-level hierarchy is designed and constructed using a large set of signature-based reasoning and grading mechanisms. This set employs likelihood functions that are built as radial-based functions from the histograms of the object instances. During classification, a probabilistic matching measure is used to search through a finite graph to find the best assignment of geometric parts to the functional structures of each class. An object is assigned to the class that provides the highest matching value. Reuse of functional primitives in different classes enables easy expansion to new categories. We tested the proposed scheme on a database of about 1000 different 3D objects. The proposed scheme achieved high classification accuracy while using small training sets.