Paper
7 January 2020 Local optimal oriented pattern for person independent facial expression recognition
Author Affiliations +
Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114330R (2020) https://doi.org/10.1117/12.2559018
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands
Abstract
Facial expressions play a key role in identifying the internal emotion state of human beings. Human beings have the tendency to recognize human emotions without any delay. But, a fully automated expression recognition by a computer is a problem that still persists. Towards solving this problem, a Local Optimal Oriented Pattern (LOOP) has been proposed in this paper. This descriptor is proposed to overcome some of the drawbacks in existing feature descriptors, Local Binary Pattern (LBP) and Local Directional Pattern (LDP) by combining the strengths of each of these two descriptors. The LOOP descriptor has been applied on JAFFE, MUG, WSEFEP and ADFES databases in person independent setup. The experiments are conducted for six, seven expressions in all the four databases. The experimental results proved that the proposed LOOP descriptor achieved a better recognition accuracy than existing methods by taking less computation time.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mukku Nisanth Kartheek, Munaga V. N. K. Prasad, and Raju Bhukya "Local optimal oriented pattern for person independent facial expression recognition", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114330R (7 January 2020); https://doi.org/10.1117/12.2559018
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KEYWORDS
Databases

Binary data

Feature extraction

Facial recognition systems

Classification systems

Computer programming

Convolutional neural networks

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