Adaptive Lip Feature Point Detection Algorithm for Real-Time Computer Vision-Based Smile Training System

This paper presents an adaptive lip feature point detection algorithm for the proposed real-time smile training system using visual instructions. The proposed algorithm can detect a lip feature point irrespective of lip color with minimal user participation, such as drawing a line on a lip on the screen. Therefore, the proposed algorithm supports adaptive feature detection by real-time analysis for a color histogram. Moreover, we develop a supportive guide model as visual instructions for the target expression. By using the guide model, users can train their smile expression intuitively because they can easily identify the differences between their smile and target expression. We also allow users to experience the smile training system using the proposed methods and we evaluated the effectiveness of these methods through usability tests. As experimental results, the proposed algorithm for feature detection had 3.4 error pixels and we found that the proposed methods could be an effective approach for training smile expressions in real-time processing.