SPATIAL WEIGHTED FISHER VECTOR FOR IMAGE RETRIEVAL
Qi,Chengzuo; Shi,Cunzhao; Xu,Jian; Wang,Chunheng; Xiao,Baihua
2017-07
Conference NameIEEE International Conference on Multimedia and Expo
Pages463 - 468
Conference Date10-14 July 2017
Conference Placehongkong
Abstract
Several recent works interpret convolutional features produced
by deep convolutional neural networks as local descriptors.
Existing high-dimensional aggregation based methods,
e.g., Fisher Vector (FV) obtain inferior performance to pooling
based methods in most situations, and we observe that
it is mainly caused by the ignorance of spatial weights. In
this paper, we propose a novel method named spatial weighted
Fisher Vector (SWFV) to enhance the representation of
FV by injecting the spatial weight map to FV. In addition,
we further analyze the distribution of spatial weights and propose
truncated spatial weighted FV (TSWFV). Experimental
results on two benchmark datasets demonstrate that the two
proposed methods achieve competitive results compared with
other global representation based methods.
KeywordFisher Vector Spatial Weight Convolu-tional Feature
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19582
Collection复杂系统管理与控制国家重点实验室_影像分析与机器视觉
AffiliationInstitute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Qi,Chengzuo,Shi,Cunzhao,Xu,Jian,et al. SPATIAL WEIGHTED FISHER VECTOR FOR IMAGE RETRIEVAL[C],2017:463 - 468.
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