| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| Feature 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. | 1.93 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Feature 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.
Description
EISBN - 978-1-4244-6921-5
Conference date - 18 July 2010 - 23 July 2010; Conference code - 82124
Conference date - 18 July 2010 - 23 July 2010; Conference code - 82124
Keywords
Pixel Engines Fuzzy sets Tracking Kalman filters Shape Acceleration
Pedagogical Context
Citation
P. Couto, N. V. Lopes, H. Bustince and P. Melo-Pinto, "Fuzzy dynamic model for feature tracking," International Conference on Fuzzy Systems, Barcelona, Spain, 2010, pp. 1-8, doi: https://doi.org/10.1109/FUZZY.2010.5583979.
Publisher
IEEE Canada
CC License
Without CC licence
