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Boosting VLAD with supervised dictionary learning and high-order statistics

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成果类型:
期刊论文、会议论文
作者:
Peng, Xiaojiang*;Wang, Limin;Qiao, Yu;Peng, Qiang
通讯作者:
Peng, Xiaojiang
作者机构:
[Peng, Qiang; Peng, Xiaojiang] Southwest Jiaotong Univ, Chengdu, Peoples R China.
[Wang, Limin] Chinese Univ Hong Kong, Dept Informat Engn, Hong Kong, Peoples R China.
[Qiao, Yu; Wang, Limin; Peng, Xiaojiang] Chinese Acad Sci, Shenzhen Key Lab CVPR, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China.
[Wang, Limin] Hengyang Normal Univ, Hengyang, Peoples R China.
通讯机构:
[Peng, Xiaojiang] S
Southwest Jiaotong Univ, Chengdu, Peoples R China.
语种:
英文
关键词:
Artificial intelligence;Computer science;Computers;Classification tasks;Dictionary learning;Dictionary learning algorithms;Efficient computation;High order statistics;Image-based objects;State-of-the-art performance;Vector of locally aggregated descriptors;Aggregates
期刊:
Lecture Notes in Computer Science
ISSN:
0302-9743
年:
2014
卷:
8691 LNCS
期:
PART 3
页码:
660-674
会议名称:
European Conference on Computer Vision
基金类别:
Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [91320101, 61036008, 60972111]; Shenzhen Basic Research Program [JC201005270350A, JCYJ20120903092050890, JCYJ201 20617114614438]; 100 Talents Program of CASChinese Academy of Sciences; Guangdong Innovative Research Team Program [201001D0104648280]; Hunan province
机构署名:
本校为其他机构
摘要:
Recent studies show that aggregating local descriptors into super vector yields effective representation for retrieval and classification tasks. A popular method along this line is vector of locally aggregated descriptors (VLAD), which aggregates the residuals between descriptors and visual words. However, original VLAD ignores high-order statistics of local descriptors and its dictionary may not be optimal for classification tasks. In this paper, we address these problems by utilizing high-order statistics of local descriptors and peforming su...

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