1. How to submit my research paper? What’s the process of publication of my paper?
The journal receives submitted manuscripts via email only. Please submit your research paper in .doc or .pdf format to the submission email: jait@etpub.com.
2.Can I submit an abstract?
The journal publishes full research papers. So only full paper submission should be considered for possible publication. Papers with insufficient content may be rejected as well, make sure your paper is sufficient enough to be published...[Read More]

Geometric-based Feature Extraction and Classification for Emotion Expressions of 3D Video Film

Salwa A. Al-agha 1, Hilal H. Saleh 2, and Rana F. Ghani 2
1. Department of Electrical Engineering, University of Technology, Baghdad, Iraq
2. Department of Computer Sciences, University of Technology, Baghdad, Iraq
Abstract—Feature extraction is the most significant step in the operation of emotion expressions recognition. Discrimination operation of emotion expressions has gained the attention of many researchers in the field of pattern recognition because of its significant impact on the various aspects of applications, especially in the application of human-computer interaction, both for the image or to the video. Based on pattern recognition theory, the process of facial expression recognition can be divided into features extraction operation and classification operation. In this paper, the geometric-based features extraction operation is used for extracting the local characteristics (landmarks) of a set of emotion expressions (anger, happiness, sadness, surprise) for images of BOSPHORUS database as training stage, then the classification operation is done by using of the threshold method (Euclidean distance) between the distances of neutral image and the expression image. The trained system is used for feature extraction and classification for 3D video film (stereoscopic) as testing stage. This method is implemented on 40 3D video films that were recorded, 10 video films for each expression of the four basic emotion; the ratio of discrimination is 85%.

Index Terms—local feature extraction, 3D video film, basic emotion expression, emotion classification, 3D video classification

Cite: Salwa A. Al-agha , Hilal H. Saleh, and Rana F. Ghani, "Geometric-based Feature Extraction and Classification for Emotion Expressions of 3D Video Film," Vol. 8, No. 2, pp. 74-79, May, 2017. doi: 10.12720/jait.8.2.74-79

Copyright © 2013-2016 Journal of Advances in Information Technology, All Rights Reserved
E-mail: jait@etpub.com