Advancements in Human Eye Micro-Expression Detection Using Convolutional Neural Networks: Database Development and Real-Time Application in Security and Education
Main Article Content
Abstract
A convolutional neural network (CNN) represents a type of artificial neural network distinguished by its efficiency in handling complex artificial intelligence tasks. It presents new opportunities for the pattern recognition of micro-expressions characterized by short duration and small movement amplitude. In the realm of micro-expression recognition research, studies focusing exclusively on eye micro-expressions are limited, yet their significance should not be underestimated. This paper's primary contributions include the creation of a database dedicated to human eye expressions. By segmenting existing facial expression databases and isolating only the eye region, a specialized micro-expression database for the human eye was established. Utilizing TensorFlow, CNN is employed to train, predict, classify, and identify facial expressions within the human eye. This approach successfully achieves micro-expression recognition in the eye area. Additionally, the integration of CUDA significantly reduces the training time of the system model.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Mind forge Academia also operates under the Creative Commons Licence CC-BY 4.0. This allows for copy and redistribute the material in any medium or format for any purpose, even commercially. The premise is that you must provide appropriate citation information.
References
Ekman P, Friesen W V. The Repertoire of Nonverbal Behavior: Categories, Origins, Usage, and Coding[J]. Semiotica, 1969, 1(1):49-98.
Information on https://www.kaggle.com
Wang S J, Chen H L, Yan W J, et al. Face recognition and micro-expression recognition based on discriminant tensor subspace analysis plus extreme learning machine [J]. Neural Processing Letters, 2014:39(1):25-43.
Sabrina Hoppe, Andreas Bulling. End-to-End Eye Movement Detection Using Convolutional Neural Networks. arXiv:1609.02452 [cs.CV].2016,09(08).
Wu Q, Shen X, Fu X. The machine knows what you are hiding: an automatic micro-expression recognition system[M]. Affective Computing and Intelligent Interaction. Springer Berlin Heidelberg, 2011: 152-162.
Shreve M, Godavarthy S, Goldgof D, et al. Macro and micro-expression spotting in long videos using spatiotemporal strain[C]. IEEE International Conference on Automatic Face & Gesture Recognition and Workshops. IEEE, 2011:51-56.
Wang S J, Yan W J, Li X B, Zhao G Y, Zhou C G, Fu XL, Yang M H, Tao J H. Micro-expression recognition usingcolor spaces. IEEE Transactions on Image Processing, 2015,24(12): 6034−6047.