Share Email Print

Proceedings Paper

Facial expression identification using 3D geometric features from Microsoft Kinect device
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

Paper Details

Date Published: 19 May 2016
PDF: 14 pages
Proc. SPIE 9869, Mobile Multimedia/Image Processing, Security, and Applications 2016, 986903 (19 May 2016); doi: 10.1117/12.2223029
Show Author Affiliations
Dongxu Han, The Univ. of Buckingham (United Kingdom)
Naseer Al Jawad, The Univ. of Buckingham (United Kingdom)
Hongbo Du, The Univ. of Buckingham (United Kingdom)

Published in SPIE Proceedings Vol. 9869:
Mobile Multimedia/Image Processing, Security, and Applications 2016
Sos S. Agaian; Sabah A. Jassim, Editor(s)

© SPIE. Terms of Use
Back to Top