Haolai Li

Papers

Total Citations

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About

Haolai Li is a researcher whose work sits at the intersection of computer vision, human-robot interaction, and intelligent systems. His most-cited paper, "Gesture recognition based on BoF and its application in human-machine interaction of service robot" (2016), introduces a novel 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 isolate gesture information from the body, then uses SURF features to enable robust, real-time interaction with service robots. While his citation count is modest, this paper represents an early and practical contribution to making human-robot communication more intuitive. Li’s research is significant for its cross-domain application of established computer vision techniques to solve emerging challenges in robotics. His work demonstrates a clear focus on bridging algorithmic theory with tangible, user-centered applications, laying groundwork for more natural and accessible human-machine interfaces. For students and researchers in robotics or computer vision, Li’s approach offers a valuable case study in adapting proven methods to new, interaction-driven problems.