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Research on User Clustering Collaborative Filtering Algorithm
Lihua Tian,Liguo Han,Junhua Yue 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.4
Memory-based CF algorithms have the weakness of low real-time ability and scalability. For these issues, a SVD-based K-means clustering CF algorithm is proposed. Traditional clustering-based CF algorithms have low recommendation precision because of data sparsity. So we first fill the missing ratings by SVD prediction, and then implement k-means clustering in the filled matix. This algorithm overcomse the data sparsity issue via SVD and keep the advantage of clustering, such as good real-time ability and scalability. Experiments results show that this algorithm outperforms Pearson CF, svd CF and k-means CF.
Dynamic Gesture Recognition based on Image Sequence
Lihua Tian,Liguo Han,Xiujuan Gu 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.12
This paper proposed an algorithm for 3D hands tracking on the learned hierarchical latent variable space, which employs a Hierarchical Gaussian Process Latent Variable Model(HGPLVM) to learn the hierarchical latent space of hands motion and the nonlinear mapping from the hierarchical latent space to the pose space simultaneously. Nonlinear mappings from the hierarchical latent space to the space of hand images are constructed using radial basis function interpolation method. With these mappings, particles can be projected into hand images and measured in the image space directly. Particle filters with fewer particles are used to track the hand on the learned hierarchical low-dimensional space. Then the Hierarchical Conditional Random Field, which can capture extrinsic class dynamics and learn the relationship between motions of hand parts and different hand gestures simultaneously, is presented to model the continuous hand gestures. Experimental results show that our proposed method can track articulated hand robustly and approving recognition performance has also been achieved on the user-defined hand gesture dataset.
Research on Image Segmentation based on Clustering Algorithm
Lihua Tian,Liguo Han,Junhua Yue 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.2
Hierarchical clustering (HC) algorithm can obtain good clustering results, but it needs large storage and computational complexity for large image processing. Anew color image segmentation algorithm based on mean shift and hierarchical clustering algorithm named MSHC is presented in this paper. MSHC algorithm preprocesses an input image by MS algorithm to form segmented regions that preserve the desirable discontinuity characteristics of image. The number of segmented regions, instead of the number of image pixels, is considered as the input data scale of HC algorithm. The proximity between each cluster is calculated to form the proximity matrix, and then ward algorithm is employed to obtain the final segmentation results. MSHC algorithm is employed on color image and medical image segmentation.