Extending evolutionary Fuzzy Quantile Inference to classify partially occluded human motions

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@InProceedings{Khoury:2010:ieee-fuzz,

• author = "Mehdi Khoury and Honghai Liu",
• title = "Extending evolutionary Fuzzy Quantile Inference to classify partially occluded human motions",
• booktitle = "IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010)",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-4244-6920-8",
• abstract = "This work presents a framework that combines the concept of Fuzzy Quantile Inference(FQI) with Genetic Programming (GP) in order to accurately classify real natural 3d human Motion Capture data. FQI is a generalisation of Fuzzy Gaussian Inference. It builds Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions, providing a suitable modelling paradigm for such noisy data. Genetic Programming (GP) is used to make a time dependent and context aware filter that improves the qualitative output of the classifier. Results show that FQI outperforms a GMM-based classifier when recognising six different boxing stances simultaneously, and that the addition of the GP based filter improves the accuracy of the FQI classifier significantly. A mechanism allowing the FQI extended framework to deal with occluded data reasonably well is also integrated.",
• DOI = "doi:10.1109/FUZZY.2010.5584623",
• notes = "WCCI 2010. Also known as \cite{5584623}",

}

Genetic Programming entries for Mehdi Khoury Honghai Liu

Citations