Properties and identification of human protein drug targets
摘要：
In this paper, a novel method for continuous human movement recognition based on fuzzy vector quantization (FVQ) and linear discriminant analysis (LDA) is proposed. We regard a movement as a unique combination of basic movement patterns, the so-called dynemes. The proposed algorithm combines FVQ and LDA to discover the most discriminative dynemes as well as represent and discriminate the different human movements in terms of these dynemes. This method allows for simple Mahalanobis or cosine distance comparison of not aligned human movements, taking into account implicitly time shifts and internal speed variations, and, thus, aiding the design of a real-time continuous human movement recognition algorithm. The effectiveness and robustness of this method is shown by experimental results on a standard dataset with videos captured under real conditions, and on a new video dataset created using motion capture data.
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关键词：
Amino Acid Sequence Binding Sites Computational Biology methods Databases, Protein Drug Discovery Humans Pharmaceutical Preparations chemistry Proteins antagonists &inhibitors chemistry Sequence Analysis, Protein
DOI：
10.1093/bioinformatics/btp002
被引量：
年份：
2009
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