ERNEST: A Semantic Network System for Pattern Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Knowledge-based image understanding systems: a survey
Computer Vision and Image Understanding
Playing Domino: A Case Study for an Active Vision System
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation
International Journal of Computer Vision
Multi-Aspect Detection of Articulated Objects
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
Model-based recognition of 2D objects in perspective images
Pattern Recognition and Image Analysis
Model-based recognition of 2D objects under perspective distortion
Pattern Recognition and Image Analysis
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This paper presents a case study showing that domino tile recognition using a model-based approach delivers results comparable to heuristic or statistical approaches. The knowledge on our models is modeled in TGraphs which are typed, attributed, and ordered directed graphs. Four task-independent rules are defined to create a domain independent control strategy which manages the object recognition. To perform the matching of elements found in the image and elements given by the model, a large number of hypotheses may arise. We designed several belief functions in terms of Dempster-Shafer in order to rate hypotheses emerging from the assignment of image to model elements. The developed system achieves a recall of 89.4% and a precision of 94.4%. As a result we are able to show that model based object recognition is on a competitive basis with the benefit of knowing the belief in each model. This enables the possibility to apply our techniques to more complex domains again, as it was tried and canceled 10 years ago.