CC-Glasses: Color Communication Support for People with Color Vision Deficiency Using Augmented Reality and Deep Learning

People who suffer from color vision deficiency (CVD) can face difficulties when communicating with others by failing to identify target objects referred by their color names. While most existing studies on CVD compensation have focused on the issue of color contrast loss. Although there are approaches can provide clues of color name to users, these techniques either require training, or cannot protect users' privacy, i.e., the fact of having CVD. In this paper, based on augmented reality (AR) and deep learning technologies, we propose a novel system to provide supporting information to users affected by CVD for color communication assistance. The state-of-the-art deep neural network (DNN) model for referring segmentation (RS) is adopted to generate supporting information, and AR glasses are utilized for information presentation. To improve the performance of the proposed system further, a new dataset is constructed based on a novel concept called Color-Object Noun Pair. The results of evaluation experiments show that the new dataset can enhance the performance of the adopted DNN model, and the proposed system can help users affected by CVD successfully identify target objects by their color names.