Anbang Yang
Papers
2
Total Citations
19
H-Index
2
About
Anbang Yang is a leading researcher in assistive navigation technology, with a primary focus on developing infrastructure-independent vision-based systems for people with blindness and low vision. Their most significant contribution is the UNav system, a pioneering vision-based navigation approach that eliminates the need for costly pre-installed sensor infrastructure, addressing a critical barrier in assistive technology deployment. This work has garnered 16 citations and represents a paradigm shift in how navigation assistance can be delivered without environmental modifications. Yang also advanced the field through the creation of the NYC-Indoor-VPR dataset, a long-term indoor visual place recognition benchmark featuring semi-automatic annotation. This resource addresses the persistent challenge of obtaining ground truth metric trajectories for training and evaluation in indoor environments, where appearance changes at various frequencies complicate localization. With 3 citations already, this dataset is becoming a valuable tool for researchers working on visual place recognition and indoor navigation. Yang's work bridges the gap between robotics localization techniques and human-centered assistive technologies, demonstrating how computer vision innovations can directly improve quality of life for individuals with visual impairments.
Research Focus
Key Achievements
Top Papers
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