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ISMAR
2007
IEEE
15 years 7 months ago
Feature Tracking for Mobile Augmented Reality Using Video Coder Motion Vectors
We propose a novel, low-complexity, tracking scheme that uses motion vectors directly from a video coder. We compare our tracking algorithm against ground truth data, and show tha...
Gabriel Takacs, Vijay Chandrasekhar, Bernd Girod, ...
ICIC
2005
Springer
15 years 7 months ago
Methods of Decreasing the Number of Support Vectors via k-Mean Clustering
This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, Guang-...
IPPS
1998
IEEE
15 years 5 months ago
Vector Prefix and Reduction Computation on Coarse-Grained, Distributed-Memory Parallel Machines
Vector prefix and reduction are collective communication primitives in which all processors must cooperate. We present two parallel algorithms, the direct algorithm and the split ...
Seungjo Bae, Dongmin Kim, Sanjay Ranka
GRC
2008
IEEE
15 years 2 months ago
Adaptive and Iterative Least Squares Support Vector Regression based on Quadratic Renyi Entropy
An adaptive and iterative LSSVR algorithm based on quadratic Renyi entropy is presented in this paper. LS-SVM loses the sparseness of support vector which is one of the important ...
Jingqing Jiang, Chuyi Song, Haiyan Zhao, Chunguo W...
ICASSP
2010
IEEE
15 years 1 months ago
Sparse signal recovery in the presence of correlated multiple measurement vectors
Sparse signal recovery algorithms utilizing multiple measurement vectors (MMVs) are known to have better performance compared to the single measurement vector case. However, curre...
Zhilin Zhang, Bhaskar D. Rao