STATIC FACE DETECTION AND EMOTION RECOGNITION WITH FPGA SUPPORT
Paul Santi-Jones, Dongbing Gu
2006
Abstract
Throughout history, spoken language and face-to-face communication have been the primary mechanics of interaction between two or more people. While processing speech, it is often advantageous to determine the emotion of the speaker in order to better understand the context of the meaning. This paper looks at our current effort at creating a static based emotion detection system, using previously used techniques along with a custom FPGA neural network to speed up recognition rates.
References
- Bassili (1979). Emotion recognition: The role of facial movement and the relative importance of upper and lower areas of the face. Journal of Personality and Social Psychology, 37:20492059.
- Cohen, I., Garg, A., and Huang, T. (2000). Emotion recognition from facial expressions using multilevel hmm.
- Cohen, I., Sebe, N., Cozman, F. G., and Huang, T. S. (2003). Semi-supervised learning for facial expression recognition. In MIR 7803: Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval, pages 17-22, New York, NY, USA. ACM Press.
- Ekman, Friesen, H. (1978). Facial Action Coding System (FACS). W.V. Consulting Psychologists Press, Palo Alto, CA, USA.
- Fasel, B. and Luettin, J. (2003). Automatic facial expression analysis: A survey.
- Hall, E. (1990). The Hidden Dimension. Bantam Doubleday Dell Publishing Group. ISBN: 0385084765.
- I. Essa, A. P. (1994). A vision system for observing and extracting facial action parameters. In Proceedings of IEEE CVPR 1994 Conference, pages 76-83, Seattle,Washington.
- Jones, P. (2003). A low-cost motion capturing and display system for home-based rehabilitation. Master's thesis, University of Essex. Available at http://www.paulsantijones.net.
- N. Kruger, M. Potzsch, C. v. M. (1997). Determination of face position and pose with a learned representation based on labelled graphs. Image and Vision Computing, 15(8):665-673.
- Rowley, H., Baluja, S., and Kanade, T. (1998). Rotation invariant neural network-based face detection.
- Santi-Jones, P. and Gu, D. (2006). Fractional floating point neural networks: An alternative neural network system for embedded systems. Still awaiting publication. Available at http://www.paul-santijones.net.
- Schneiderman, H. (2000). A statistical approach to 3d object detection applied to faces and cars.
- Sung, K. K. and Poggio, T. (1998). Example-based learning for view-based human face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(1):39-51.
- Viola, P. and Jones, M. (2002). Robust real-time object detection. International Journal of Computer Vision - to appear.
- Wikipedia (2006). Wikipedia entry. http://en.wikipedia.org/ wiki/IMAX.
Paper Citation
in Harvard Style
Santi-Jones P. and Gu D. (2006). STATIC FACE DETECTION AND EMOTION RECOGNITION WITH FPGA SUPPORT . In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 390-397. DOI: 10.5220/0001205903900397
in Bibtex Style
@conference{icinco06,
author={Paul Santi-Jones and Dongbing Gu},
title={STATIC FACE DETECTION AND EMOTION RECOGNITION WITH FPGA SUPPORT},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={390-397},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001205903900397},
isbn={978-972-8865-60-3},
}
in EndNote Style
TY - CONF
JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - STATIC FACE DETECTION AND EMOTION RECOGNITION WITH FPGA SUPPORT
SN - 978-972-8865-60-3
AU - Santi-Jones P.
AU - Gu D.
PY - 2006
SP - 390
EP - 397
DO - 10.5220/0001205903900397