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- Title
Face image retrieval based on shape and texture feature fusion.
- Authors
Lu, Zongguang; Yang, Jing; Liu, Qingshan
- Abstract
Humongous amounts of data bring various challenges to face image retrieval. This paper proposes an efficient method to solve those problems. Firstly, we use accurate facial landmark locations as shape features. Secondly, we utilise shape priors to provide discriminative texture features for convolutional neural networks. These shape and texture features are fused to make the learned representation more robust. Finally, in order to increase efficiency, a coarse-tofine search mechanism is exploited to efficiently find similar objects. Extensive experiments on the CASIAWebFace, MSRA-CFW, and LFW datasets illustrate the superiority of our method.
- Subjects
IMAGE retrieval; IMAGE servers; ARTIFICIAL neural networks; FACE perception; IMAGE databases
- Publication
Computational Visual Media, 2017, Vol 3, Issue 4, p359
- ISSN
2096-0433
- Publication type
Article
- DOI
10.1007/s41095-017-0091-7