Pain-awareness multistream convolutional neural network for pain estimation

In medical institutions, pain is one of the important clues for patients to transmit their conditions effectively, which makes the estimation of pain status an exceedingly important task. Of late, many methods have been proposed to address this task. However, most of them estimate the pain from entire face images or videos instead of paying more attention to the regions most relevant to pain. We propose a pain-awareness multistream convolutional neural network (CNN) for pain estimation. Specifically, we separate the regions most relevant to the pain expression, and the multistream CNN is used to learn the corresponding pain-awareness features. These features are combined into pain features with adaptive weights to estimate the intensity of pain. Extensive experiments on the publicly available pain database indicate that our multistream CNN-based method has achieved inspiring results compared to the state-of-the-art technologies.