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- W2367020531 abstract "The recognition based on vision to extract features from abnormal human behaviors usually utilize straightforward sharp movement information or traditional PCA methods.The former lacks of information and the latter has ignored nonlinear information in data.Therefore,this paper will use KPCA in recognizing abnormal human behaviors to solve the aforementioned problems.Since KPCA has some defects in extracting feature abnormal behaviors,W2KPCA-KNN algorithm is proposed,which is to do weighting in both feature extraction and classification respectively.While retaining behavioral information in the image,it improves recognition accuracy and satisfies the technical requirements for abnormal behavior recognition system.The experimental comparisons show that this algorithm outperforms traditional KPCA and K-Nearest Neighbor classifier on both feature extraction and classification." @default.
- W2367020531 created "2016-06-24" @default.
- W2367020531 creator A5052081898 @default.
- W2367020531 date "2011-01-01" @default.
- W2367020531 modified "2023-09-27" @default.
- W2367020531 title "Abnormal Human Behaviors Recognition Based on W2KPCA-KNN Algorithm" @default.
- W2367020531 hasPublicationYear "2011" @default.
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