标题： 用户在循环视图采样与误差峰值可视化 显示英文标题

标题： User-in-the-Loop View Sampling with Error Peaking Visualization

摘要： 增强现实（AR）提供了可视化缺失视图样本的方法，用于新视图合成。 现有方法为新视图样本提供3D注释，并让用户通过对齐AR显示来拍摄图像。 这项数据收集任务被认为具有心理负担，并且由于理想但限制性的底层采样理论，将捕捉区域限制在预定义的小区域。 为了使用户摆脱3D注释和有限场景探索，我们提出使用局部重建的光场并可视化需要通过插入新视图来消除的错误。 我们的结果表明，误差峰值可视化方法更具包容性，减少了最终结果的失望感，并在我们的移动视图合成系统中用更少的视图样本即可获得满意的结果。 我们还表明，我们的方法可以有助于更大场景的辐射场重建，例如3D高斯点云。 显示英文摘要

摘要： Augmented reality (AR) provides ways to visualize missing view samples for novel view synthesis. Existing approaches present 3D annotations for new view samples and task users with taking images by aligning the AR display. This data collection task is known to be mentally demanding and limits capture areas to pre-defined small areas due to the ideal but restrictive underlying sampling theory. To free users from 3D annotations and limited scene exploration, we propose using locally reconstructed light fields and visualizing errors to be removed by inserting new views. Our results show that the error-peaking visualization is less invasive, reduces disappointment in final results, and is satisfactory with fewer view samples in our mobile view synthesis system. We also show that our approach can contribute to recent radiance field reconstruction for larger scenes, such as 3D Gaussian splatting.