LandmarkLens：为混合现实城市探索预测并呈现有效地标
LandmarkLens: Predicting and Presenting Effective Landmarks for Mixed-Reality Urban Exploration
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中文总结 AI 辅助
该研究针对方向感差人群空间导航困难问题，构建混合现实导航系统LandmarkLens，经实验验证其可提升方向感差者的场景识别性能，助力空间知识获取。
中文摘要 AI 辅助
方向感差（SOD）的人难以构建用于有效空间导航的认知地图，而现有导航工具优先考虑效率而非空间学习。为了解导航策略如何随能力不同而变化，我们开展了一项地标注意力研究，20名参与者（10名方向感好、10名方向感差）在虚拟现实（VR）中导航东京的四个社区。我们发现两组在注视行为和口头识别为有效的地标类型上存在系统性差异。基于这些发现，我们构建了LandmarkLens，这是一个混合现实（MR）导航系统，使用视觉语言模型（VLM）识别并突出与导航相关的地标。后续对8名方向感差的参与者的研究显示，场景识别性能有所提升，表明引导性地标注意力可支持方向感差的人获取地标级空间知识，这是迈向更广泛空间学习的第一步。
英文摘要
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.
发表机构
- The University of Tokyo（东京大学）
机构由 AI 辅助整理，请以论文原文为准。
