Abstract In this paper, we present a novel scene interpretation method by unified modeling of visual context using a hierarchical graphical model. Scene interpretation through object recognition is difficult due to several sources of ambiguity (blur, clutter). We model the visual context of scene, object, and part to disambiguate them during recognition. A precisely designed hierarchical graphical model can represent the contexts in a unified way. We also propose a new inference method, particle-based belief propagation, optimized to scene interpretation in this hierarchical graphical model. Such an inference method suits the high-level context of scene interpretation. In addition, our core inference is so general that it can be used in any complex inference problems. Experimental results validate the power of the proposed model of visual context to solve the ambiguities in scene interpretation.
Scene Interpretation: Unified Modeling of Visual Context by Particle-Based Belief Propagation in Hierarchical Graphical Model
Computer Vision – ACCV 2006 ; 8 ; 963-972
Lecture Notes in Computer Science ; 3852 , 8
2006-01-01
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Object Recognition , Graphical Model , Compatibility Function , Visual Context , Object Node Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence (incl. Robotics) , Algorithm Analysis and Problem Complexity
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