Rongtian Huo

Chongqing University of Posts and Telecommunications

Papers

Total Citations

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About

Rongtian Huo is a researcher at the forefront of computer vision and human-robot interaction, specializing in 3D human pose estimation from video. His work bridges the gap between visual perception and interactive systems, enabling machines to understand and respond to human movement in real time. Huo’s most-cited paper, “3D Human Pose Estimation in Video for Human-Computer/Robot Interaction” (2023), has garnered 15 citations, reflecting its timely contribution to the field. This research introduces robust methods for tracking body poses in dynamic environments, directly applicable to assistive robotics, virtual reality, and gesture-based control. By focusing on video-based estimation rather than static images, Huo addresses critical challenges in occlusion handling and temporal consistency, making his approach practical for real-world deployment. His work has implications for safer human-robot collaboration and more intuitive user interfaces. As an emerging voice in this interdisciplinary domain, Huo continues to push boundaries, with his research laying groundwork for next-generation interactive systems that seamlessly integrate human motion into digital and robotic contexts.