NDLI: Perception driven 3D facial expression analysis based on reverse correlation and normal component

Content Provider	IEEE Xplore Digital Library
Author	Xing Zhang Zheng Zhang Lijun Yin Hipp, D. Gerhardstein, P.
Copyright Year	2015
Abstract	Research on automated facial expression analysis (FEA) has been focused on applying different feature extraction methods on texture space and geometric space, using holistic or local facial regions based on regular grids or facial anatomical structure. Not much work has been investigated by taking human perception into account. In this paper, we propose to study the facial expressive regions using a reverse correlation method, and further develop a novel 3D local normal component feature representation based on human perceptions. The classification image (CI) accumulated in multiple trials reveals the shape features which alter the neutral Mona Lisa portrait to positive and negative domains. The differences can be identified by both humans and machine. Based on the CI and the derived local feature regions, a novel 3D normal component based feature (3D-NLBP) is proposed to represent positive and negative expressions (e.g., happiness and sadness). This approach achieves a good performance and has been validated by testing on both high-resolution database and real-time low resolution depth map videos.
Starting Page	616
Ending Page	622
File Size	3284578
Page Count	7
File Format	PDF
ISSN	21568111
e-ISBN	9781479999538
DOI	10.1109/ACII.2015.7344633
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	3D facial expression recognition Correlation Three-dimensional displays Face recognition Observers Feature extraction Reverse correlation Face Normal component Videos
Content Type	Text
Resource Type	Article

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