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This paper describes a scalable method of estimating a vision graph, in which a pair of camera nodes are connected by an edge if the two nodes share the same field of view, based on local image feature correspondences. The proposed method is implemented in a distributed fashion, meanwhile avoiding the flooding of the image feature information since it can be a bottleneck in achieving scalability....
A rapid algorithm for eye state detection is proposed in this paper. It takes use of gray scale characteristics of the eye and upper eyelid bending direction to distinguish the open and closed eye states. Circle similarity of region is proposed as an index to characterize the eye state. And a simple method based on the relation of curve and the straight line linking the two endpoints of curve is proposed...
Adaptive local binary patterns method is proposed in this paper, on which an effective fabric defect detection algorithm is designed. ALBP method selects the frequently occurred patterns to construct the main pattern set, which avoids using the same pattern set to describe different texture structures in uniform local binary patterns method. The features of free defect image are extracted according...
Discrete wavelet transform (DWT) provides a multiresolution view of hyperspectral data. This paper proposes a method to combine the wavelet features at different layers to improve the classification accuracy of hyperspectral data, where both global and local spectral features could be exploited. After feature extraction using DWT, the wavelet feature set of each layer is processed independently by...
In this paper, a method of ECoG identification based on SVM ensemble was proposed to solve the problems of low classification accuracy and weak robustness for ECoG collection during different period of time. Common spatial pattern (CSP) algorithm is used for feature extraction, and support vector machine (SVM) ensemble is applied for classification of ECoG. Besides, bagging algorithm and cross-validation...
The Common Spatial Pattern (CSP) algorithm is a popular method for efficiently calculating spatial filters. However, several previous studies show that CSP's performance deteriorates especially when the number of channels is large compared to small number of training datasets. As a result, it is necessary to choose an optimal subset of the whole channels to save computational time and retain high...
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