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In order to get better semantic annotation performance, block-global features are extracted as low-level visual features for image semantic annotation. Specifically, wellknown global feature extraction method, namely two-dimensional principal component analysis (2DPCA) is applied to extract the image block-global features. Unlike typical image annotation methods which use local features or global...
We present a new feature extraction method, which called the complete two-dimensional principal component analysis (Complete 2DPCA), for image registration. Complete 2DPCA is based on 2D image matrices. Two image covariance matrices are constructed directly using the original image matrix and their eigenvectors are derived for image feature extraction. In the 2D image registration scheme, we propose...
Analyzing notor imagery electrocardiogram (ECoG) signal is very challenging for it is hard to set up a classifier based on the labeled ECoG obtained in the first session and apply it to the unlabeled test data obtained in the second session. Here we propose a new approach to analyze ECoG trails in the case of session-to-session transfer exists. In our approach, firstly, dimension reduction is performed...
Face recognition often suffers from the small sample size problem. Regularization is one of the solutions to this problem. In this paper, we investigate the Kullback-Leibler information measure (KLIM) based regularization classifiers for face recognition. Two parameter estimation approaches including the cross-validation technique and model selection criterion are chosen to optimize the regularization...
As a kind of powerful anti-counterfeiting device, diffractive optically variable image (DOVI) has been developed and widely used in information security field. However, the identification of DOVI today by bare eyes is not reliable. In this paper we investigate the recognition of DOVI with machine learning method, and five kinds of algorithms, namely quadratic discriminate analysis (QDA), linear discriminate...
In this paper, we propose an intelligent surveillance system which can detect human, recognize certain postures and activities, and send out informing SMS messages when abnormal activities are detected. Nine static postures can be recognized using universal eigenspace technique and projection histogram matching method. After recognizing static postures, Hidden Markov Models are used to recognize human...
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