Zhao Huang

Queen Mary University of London, Northumbria University

Papers

Total Citations

H-Index

About

Zhao Huang is a researcher at the forefront of computer vision and augmented reality, with a primary focus on advancing image-based localization and pose estimation technologies. Their work addresses the critical challenge of enabling accurate, real-time spatial understanding for applications ranging from navigation to human-computer interaction. Huang’s most cited paper, "A critical analysis of image-based camera pose estimation techniques" (2023), with 44 citations, provides a comprehensive evaluation of state-of-the-art methods, offering essential insights for researchers and practitioners in the field. Building on this foundation, their recent work "ARLO: Augmented Reality Localization Optimization for Real-Time Pose Estimation and Human–Computer Interaction" (2025) introduces novel optimization strategies that enhance the performance of platforms like Apple’s ARKit, which relies on visual-inertial odometry and SLAM algorithms. This contribution demonstrates Huang’s ability to bridge theoretical analysis with practical, real-world applications, pushing the boundaries of what is possible in outdoor AR environments. With a growing citation record and a clear trajectory toward impactful, applied research, Zhao Huang is establishing themselves as a key voice in the evolution of augmented reality and spatial computing technologies.