IEICE TRANSACTIONS on Information
Action Recognition Using Weighted Locality-Constrained Linear Coding
Summary :
Recently, locality-constrained linear coding (LLC) as a coding strategy has attracted much attention, due to its better reconstruction than sparse coding and vector quantization. However, LLC ignores the weight information of codewords during the coding stage, and assumes that every selected base has same credibility, even if their weights are different. To further improve the discriminative power of LLC code, we propose a weighted LLC algorithm that considers the codeword weight information. Experiments on the KTH and UCF datasets show that the recognition system based on WLLC achieves better performance than that based on the classical LLC and VQ, and outperforms the recent classical systems.
- Publication
- IEICE TRANSACTIONS on Information Vol.E98-D No.2 pp.462-466
- Publication Date
- 2015/02/01
- Publicized
- 2014/10/31
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDL8134
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Jiangfeng YANG
University of Electronic Science and Technology of China
Zheng MA
University of Electronic Science and Technology of China
Keyword
Latest Issue
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Jiangfeng YANG, Zheng MA, "Action Recognition Using Weighted Locality-Constrained Linear Coding" in IEICE TRANSACTIONS on Information,
vol. E98-D, no. 2, pp. 462-466, February 2015, doi: 10.1587/transinf.2014EDL8134.
Abstract: Recently, locality-constrained linear coding (LLC) as a coding strategy has attracted much attention, due to its better reconstruction than sparse coding and vector quantization. However, LLC ignores the weight information of codewords during the coding stage, and assumes that every selected base has same credibility, even if their weights are different. To further improve the discriminative power of LLC code, we propose a weighted LLC algorithm that considers the codeword weight information. Experiments on the KTH and UCF datasets show that the recognition system based on WLLC achieves better performance than that based on the classical LLC and VQ, and outperforms the recent classical systems.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDL8134/_p
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@ARTICLE{e98-d_2_462,
author={Jiangfeng YANG, Zheng MA, },
journal={IEICE TRANSACTIONS on Information},
title={Action Recognition Using Weighted Locality-Constrained Linear Coding},
year={2015},
volume={E98-D},
number={2},
pages={462-466},
abstract={Recently, locality-constrained linear coding (LLC) as a coding strategy has attracted much attention, due to its better reconstruction than sparse coding and vector quantization. However, LLC ignores the weight information of codewords during the coding stage, and assumes that every selected base has same credibility, even if their weights are different. To further improve the discriminative power of LLC code, we propose a weighted LLC algorithm that considers the codeword weight information. Experiments on the KTH and UCF datasets show that the recognition system based on WLLC achieves better performance than that based on the classical LLC and VQ, and outperforms the recent classical systems.},
keywords={},
doi={10.1587/transinf.2014EDL8134},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - Action Recognition Using Weighted Locality-Constrained Linear Coding
T2 - IEICE TRANSACTIONS on Information
SP - 462
EP - 466
AU - Jiangfeng YANG
AU - Zheng MA
PY - 2015
DO - 10.1587/transinf.2014EDL8134
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2015
AB - Recently, locality-constrained linear coding (LLC) as a coding strategy has attracted much attention, due to its better reconstruction than sparse coding and vector quantization. However, LLC ignores the weight information of codewords during the coding stage, and assumes that every selected base has same credibility, even if their weights are different. To further improve the discriminative power of LLC code, we propose a weighted LLC algorithm that considers the codeword weight information. Experiments on the KTH and UCF datasets show that the recognition system based on WLLC achieves better performance than that based on the classical LLC and VQ, and outperforms the recent classical systems.
ER -
English
