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The feature vector is composed of multiple characteristics which can reflect fault information of the rolling bearing. In order to quantify the sensitivity of features for fault diagnosis, the quantitative problem is transformed into the sparse representation problem based on the sparse representation theory. Since the feature vector sparseness is unknown, a sparse dictionary is constructed based...
Sound is only the important way of human perception on the world, but also reflects some important characteristics of human behaviors under certain circumstances. This paper mainly presents the sound event recognition method using Mel-frequency Morlet wavelet subband (MFMWS) feature and sparse representation-based classifier (SRC) aiming at security monitoring applications. In order to evaluate its...
This paper proposes a boosted co-training algorithm for human action recognition. To address the view-sufficiency and view-dependency issues in co-training, two new confidence measures, namely, inter-view confidence and intra-view confidence, are proposed. They are dynamically fused into a semi-supervised learning process. Mutual information is employed to quantify the inter-view uncertainty and measure...
A novel approach for detecting anomaly in visual surveillance system is proposed in this paper. It is composed of three parts:(a) a dense motion field and motion statistics method, (b) one-class SVM for one-class classification, (c) motion directional PCA for feature dimensionality reduction. Experiments demonstrate the effectiveness of proposed algorithm in detecting abnormal events in surveillance...
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