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Facial Expression Recognition using 1D Transform Features and Hidden Markov Model

  • Jalal, Ahmad (Dept. of Computer Science, Air University) ;
  • Kamal, Shaharyar (Dept. of Electronics and Radio Engineering, Kyung Hee University) ;
  • Kim, Daijin (Dept. of Computer Science and Engineering, POSTECH)
  • Received : 2015.10.16
  • Accepted : 2017.04.05
  • Published : 2017.07.01

Abstract

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

Acknowledgement

Supported by : Ministry of Trade, Industry and Energy

References

  1. M. Wimmer, B. MacDonald, D. Jayamuni and A. Yadav, "Facial expression recognition for humanrobot interaction: a prototype," in Proceedings of RobVis Conference, Auckland, pp.139-152, Feb. 2008.
  2. A. Jalal and S. Kim, "Global security using human face understanding under vision ubiquitous architectture system," World academy of science, engineering and technology, vol. 13, pp.7-11, 2006.
  3. A. Jalal and I. Uddin, "Security architecture for third generation (3G) using GMHS cellular network," in Proceedings of ICET, PK, pp.74-79, Nov. 2007.
  4. S. Kamal and A. Jalal, "A hybrid feature extraction approach for human detection, tracking and activity recognition using depth sensors," Arabian Journal for science and engineering, 2015.
  5. A. Jalal and Y. Rasheed, "Collaboration achievement along with performance maintenance in video streaming," in Proceedings of ICL, Austria, pp. 1-8, Sep. 2007.
  6. A. Jalal, S. Kamal and D. Kim, "A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments," Sensors, vol. 14, pp. 11735-11759, 2014. https://doi.org/10.3390/s140711735
  7. A. Jalal, N. Sharif, J. Kim and T. Kim, "Human activity recognition via recognized body parts of human depth silhouettes for residents monitoring services at smart homes," Indoor and built environment, vol. 22, pp. 271-279, 2013. https://doi.org/10.1177/1420326X12469714
  8. A. Jalal and S. Kim, "Algorithmic implementation and efficiency maintenance of real-time environment using low-bitrate wireless communication," in Proceedings of SEUS, Korea, Apr. 2006.
  9. A. Kapoor, W. Burleson and R. Picard, "Automatic prediction of frustration," International Journal of human-computer studies, vol. 65, pp. 724-736, 2007. https://doi.org/10.1016/j.ijhcs.2007.02.003
  10. A. Jalal, S. Lee, J. Kim and T. Kim, "Human activity recognition via the features of labeled depth body parts," in Proceedings of ICOST, Italy, pp. 246-249, Jun. 2012.
  11. A. Jalal, J. Kim and T. Kim, "Development of a life logging system via depth imaging-based human activity recognition for smart homes," in Proceedings of SHB, Korea, pp. 91-95, Oct. 2012.
  12. A. Farooq, A. Jalal and S. Kamal, "Dense RGB-D Map-Based Human Tracking and Activity Recognition using Skin Joints Features and Self-Organizing Map," KSII transactions on internet and information systems, vol. 9, pp. 1856-1869, 2015.
  13. A. Jalal, Y. Kim, S. Kamal, A. Farooq and D. Kim, "Human daily activity recognition with joints plus body features representation using Kinect sensor," in Proceedings of ICIEV, Japan, pp. 1-6, Jun. 2015.
  14. A. Jalal, and S. Kamal, "Real-Time Life Logging via a Depth Silhouette-based Human Activity Recognition System for Smart Home Services," in Proceedings of AVSS, Korea, pp. 74-80, Aug. 2014.
  15. A. Jalal, and Y. Kim, "Dense Depth Maps-based Human Pose Tracking and Recognition in Dynamic Scenes Using Ridge Data," in Proceedings of AVSS, Korea, pp.119-124, Aug. 2014.
  16. A. Jalal and A. Shahzad, "Multiple facial feature detection using vertex modeling structure," in Proceedings of ICL, Austria, pp.1-7, Sep. 2007.
  17. A. Jalal and S. Kim, "Advanced performance achievement using multi-algorithmic approach of video transcoder for low bit rate wireless communication," ICGST journal, vol. 5, no. 9, pp. 27-32, 2005.
  18. A. Jalal, S. Kamal and D. Kim, "Depth Silhouettes Context: A new robust feature for human tracking and activity recognition based on embedded HMMs," in Proceedings of URAI, Korea, pp. 294-299, Oct. 2015.
  19. A. Jalal, S. Kamal and D. Kim, "Individual Detection-Tracking-Recognition using depth activity images," in Proceedings of URAI, Korea, pp. 450-455, Oct. 2015.
  20. A. Jalal, Y. Kim and D. Kim, "Ridge body parts features for human pose estimation and recognition from RGB-D video data," in Proceedings of ICCCNT Conference, China, pp. 1-6, Jul. 2014.
  21. A. Jalal, S. Kamal and D. Kim, "Depth Map-based Human Activity Tracking and Recognition Using Body Joints Features and Self-Organized Map," in Proceedings of ICCCNT, China, pp. 1-6, Jul. 2014.
  22. A. Jalal, S. Kamal and D. Kim, "Shape and motion features approach for activity tracking and recognition from Kinect video camera," in Proceedings of WAINA Conference, Korea, pp. 445-450, Mar. 2015.
  23. A. Jalal and M. Zeb, "Security enhancement for elearning portal," Journal of computer science and network security, vol. 8, no. 3, pp. 41-45, 2008.
  24. A. Jalal and M. Zeb, "Security and QoS optimization for distributed real time environment," in Proceedings of CIT Conference, Japan, pp. 369-374, Oct. 2007.
  25. A. Jalal, J. Kim and T. Kim, "Human activity recognition using the labeled depth body parts information of depth silhouettes," in Proceedings of SHB, Korea, pp. 1-8, Oct. 2012.
  26. F. S. Samaria, and A. C. Harter, "Parameterization of a stochastic model for human face identification," in Proceedings of WACV, USA, pp. 138-142, Dec. 1994.