Facial Expression Recognition Using Kinect Depth Sensor and Convolutional Neural Networks

Ijjina, E P and C, Krishna Mohan (2014) Facial Expression Recognition Using Kinect Depth Sensor and Convolutional Neural Networks. In: 13th International Conference on Machine Learning and Applications (ICMLA), 3-6 December, 2014, Detroit, MI.

Full text not available from this repository. (Request a copy)


Facial expression recognition is an active area of research with applications in the design of Human Computer Interaction (HCI) systems. In this paper, we propose an approach for facial expression recognition using deep convolutional neural networks (CNN) based on features generated from depth information only. The Gradient direction information of depth data is used to represent facial information, due its invariance to distance from the sensor. The ability of a convolutional neural networks (CNN) to learn local discriminative patterns from data is used to recognize facial expressions from the representation of unregistered facial images. Experiments conducted on EURECOM kinect face dataset demonstrate the effectiveness of the proposed approach

[error in script]
IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: convolutional neural networks (CNN); Facial expression recognition
Subjects: Computer science > Computer programming, programs, data
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 30 Nov 2015 11:41
Last Modified: 01 Sep 2017 09:23
URI: http://raiith.iith.ac.in/id/eprint/2047
Publisher URL: https://doi.org/10.1109/ICMLA.2014.70
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 2047 Statistics for this ePrint Item