Micro Expression Detection and Recognition from High Speed Cameras using Convolutional Neural Networks

In this paper, we propose a micro-expression detection and recognition framework based on convolutional neural networks. This paper presents the following contributions: the relevant features are learned by a convolutional neural network that uses as input difference images of three equally spaced frames from the video sequence, capturing important motion information. Next, a sliding time window is used to iterate through the video sequence and the output of the network in order to eliminate false positives. The method was trained using images from two publicly available micro-expression databases. The effectiveness of the proposed solution is demonstrated by the experiments we performed, from which a recognition rate of 72.22% was obtained.