Browsing by Author "Couto, Pedro"
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- Fuzzy dynamic model for feature trackingPublication . Couto, Pedro; Lopes, Nuno Vieira; Bustince, Humberto; Melo-Pinto, PedroFeature tracking is one of the most challenging and important tasks in Motion Analysis which plays an important role in several areas of Computer Vision. In this work, a novel approach for feature tracking based on Fuzzy concepts is introduced. Fuzzy Sets related with both cinematic (movement model) and non cinematic (image gray levels) properties are constructed in order to model the feature motion. Meanwhile cinematic related fuzzy sets model the feature movement characteristics, the non cinematic fuzzy sets model the feature visible image related properties. The final motion model is obtained through the fusion of these fuzzy models by means of a fuzzy inference engine. Experimental results are presented showing that the approach successfully copes with usual difficulties within this problem.
- Multi-feature Tracking Approach Using Dynamic Fuzzy SetsPublication . Lopes, Nuno Vieira; Couto, Pedro; Melo-Pinto, PedroIn this paper a new tracking approach based in fuzzy concepts is introduced. The aim of this methodology is to incorporate in the proposed model the uncertainty underlying any problem of feature tracking, through the use of fuzzy sets. Several dynamic fuzzy sets are constructed according both cinematic (movement model) and non cinematic properties (image gray levels) that distinguish the feature. Meanwhile cinematic related fuzzy sets model the feature movement characteristics, the non cinematic fuzzy sets model the feature visible image related properties. The tracking task is performed through the fusion of these fuzzy models by means of a fuzzy inference engine. This way feature detection and matching steps are performed exclusively using inference rules on fuzzy sets.