Problem
Research questions and friction points this paper is trying to address.
poor sense of direction
spatial navigation
landmark attention
LandmarkLens: Predicting and Presenting Effective Landmarks for Mixed-Reality Urban Exploration
🤖 AI Summary
研究针对方向感差的人群在空间导航中的困难，通过分析不同人群对地标的关注差异，开发了LandmarkLens系统，利用视觉-语言模型识别并强调重要地标，以帮助用户提高空间认知能力。
📝 Abstract
People with a poor sense of direction (SOD) struggle to build cognitive maps for effective spatial navigation, and existing navigation tools prioritize efficiency over spatial learning. To understand how navigation strategies differ by ability, we conducted a landmark attention study with 20 participants (ten good SOD, ten poor SOD) who navigated across four Tokyo neighborhoods in virtual reality (VR). We found systematic group differences in both gaze behavior and the types of landmarks they verbally identify as effective. Based on these findings, we built LandmarkLens, a mixed-reality (MR) navigation system that uses a vision-language model (VLM) to identify and highlight navigation-relevant landmarks. A follow-up study with eight poor-SOD participants showed improved performance in scene recognition, suggesting that guided landmark attention can support landmark-level spatial knowledge acquisition for people with poor SOD, a first step toward broader spatial learning.
Innovation
Methods, ideas, or system contributions that make the work stand out.
LandmarkLens
vision-language model
mixed-reality navigation
spatial learning
landmark attention
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