Disguised Face Identification (DFI) with Facial KeyPoints Using Spatial Fusion Convolutional Network

Disguised face identification (DFI) is an extremely challenging problem due to the numerous variations that can be introduced using different disguises. This paper introduces a deep learning framework to first detect 14 facial key-points which are then utilized to perform disguised face identificati...

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Bibliographic Details
Published in2017 IEEE International Conference on Computer Vision Workshops (ICCVW) pp. 1648 - 1655
Main Authors Singh, Amarjot, Patil, Devendra, Reddy, G. Meghana, Omkar, S.N.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Face
Glass
Heating systems
Lips
Machine learning
Training
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Summary:Disguised face identification (DFI) is an extremely challenging problem due to the numerous variations that can be introduced using different disguises. This paper introduces a deep learning framework to first detect 14 facial key-points which are then utilized to perform disguised face identification. Since the training of deep learning architectures relies on large annotated datasets, two annotated facial key-points datasets are introduced. The effectiveness of the facial keypoint detection framework is presented for each keypoint. The superiority of the key-point detection framework is also demonstrated by a comparison with other deep networks. The effectiveness of classification performance is also demonstrated by comparison with the state-of-the-art face disguise classification methods.
ISSN:2473-9944
DOI:10.1109/ICCVW.2017.193