Autonomous driving paper index
Designing and Evaluating Scalable Mid-Air Gestures forInteractive Systems
One-line summary
As pervasive computing environments such as smart homes, in-vehicle systems, and AR/VR applications become more widespread, traditional input modalities face increasing limitations.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
As pervasive computing environments such as smart homes, in-vehicle systems, and AR/VR applications become more widespread, traditional input modalities face increasing limitations. Mid-air gestural interaction offers a complementary input modality but remains challenged by inconsistent gesture vocabularies, limited understanding of gesture execution and variability, and a lack of ecologically valid studies. This dissertation investigates how to design and evaluate mid-air gestures as a reliable input modality across pervasive computing environments by (1) analyzing gesture consistency across domains, (2) exploring user preferences for gesture use in smart homes, and (3) developing a publicly available multimodal dataset to examine gesture execution and variability. The findings provide empirical evidence and methodological resources that support the design of robust, intuitive, consistent, and transferable mid-air interaction techniques.
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