[[abstract]]The encoding process of vector quantization (VQ) is computational complex and time consuming. Compared with traditional Euclidean distance computation, some geometric properties can generate approximations with simpler computation and filter out impossible codevectors to reduce computation time. In this paper, we introduce a new approximation adopting orthogonal projection on a hyperplane for speed-up VQ encoding. Experimental results show that our proposed scheme requires only 2.7~23.2% of actual Euclidean distance calculation in the full searching. Having been proved, our proposed scheme requires only 30.1~40.3% of computation time that other recently proposed schemes need
Nearest neighbor searching is an important geometric subproblem in vector quanti-zation. Existing st...
A recently proposed product quantization method is efficient for large scale approximate nearest nei...
[[abstract]]Vector quantization (VQ) is an elementary technique for image compression. However, sear...
[[abstract]]The encoding process of vector quantization (VQ) is indeed computational complex and tim...
[[abstract]]In order to speed up the computation time of searching the closest codeword in VQ compre...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
This paper introduces an arbitrary hyperplane approach for both codebook generation and search for v...
Increasing sizes of databases and data stores mean that the traditional tasks, such as locating a ne...
[[abstract]]Vector quantization (VQ) technique is a well known method in image compression. Employin...
We propose an approximate nearest neighbor search method based on quantization. It uses, in particul...
Abstract—In this work, we consider two fast nearest-neighbor search methods based on the projections...
Nearest neighbor searching is an important geometric subproblem in vector quantization. Existing stu...
Nearest neighbor searching is an important geometric subproblem in vector quanti-zation. Existing st...
A recently proposed product quantization method is efficient for large scale approximate nearest nei...
[[abstract]]Vector quantization (VQ) is an elementary technique for image compression. However, sear...
[[abstract]]The encoding process of vector quantization (VQ) is indeed computational complex and tim...
[[abstract]]In order to speed up the computation time of searching the closest codeword in VQ compre...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
[[abstract]]One of the major difficulties arising in vector quantization (VQ) is high encoding time ...
This paper introduces an arbitrary hyperplane approach for both codebook generation and search for v...
Increasing sizes of databases and data stores mean that the traditional tasks, such as locating a ne...
[[abstract]]Vector quantization (VQ) technique is a well known method in image compression. Employin...
We propose an approximate nearest neighbor search method based on quantization. It uses, in particul...
Abstract—In this work, we consider two fast nearest-neighbor search methods based on the projections...
Nearest neighbor searching is an important geometric subproblem in vector quantization. Existing stu...
Nearest neighbor searching is an important geometric subproblem in vector quanti-zation. Existing st...
A recently proposed product quantization method is efficient for large scale approximate nearest nei...
[[abstract]]Vector quantization (VQ) is an elementary technique for image compression. However, sear...