Mingchao Li

Papers

Total Citations

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About

Mingchao Li is a researcher whose work centers on human-machine interaction, computer vision, and gesture recognition technologies, with a particular focus on enhancing service robot capabilities. His most cited paper, "Gesture recognition based on BoF and its application in human-machine interaction of service robot" (2016), introduces an innovative approach that adapts the Bag of Features (BoF) algorithm—traditionally used in target recognition and image retrieval—to the domain of hand gesture recognition. In this work, Li employs an HSV skin color adaptive method to effectively segment gesture information from the body, combined with SURF features for robust recognition. Although his citation count is modest at 3, this foundational contribution demonstrates his early engagement with practical, real-world applications of machine learning in robotics. Li’s research bridges the gap between algorithmic theory and tangible human-robot interaction, offering insights that could improve how service robots interpret and respond to human commands. His work is particularly relevant for students and researchers exploring gesture-based interfaces, computer vision pipelines, and the integration of feature extraction methods into interactive systems.