With the development of eXtended Reality (XR), head-mounted shooting and display technology have experienced significant advancement and gained considerable attention. Egocentric spatial images and videos are emerging as a compelling form of stereoscopic XR content. Different from traditional 2D images, egocentric spatial images present challenges for perceptual quality assessment due to their special shooting, processing methods, and stereoscopic characteristics. However, the corresponding image quality assessment (IQA) research for egocentric spatial images is still lacking. In this paper, we establish the Egocentric Spatial Images Quality Assessment Database (ESIQAD), the first IQA database dedicated for egocentric spatial images as far as we know. Our ESIQAD includes 500 egocentric spatial images, containing 400 images captured with the Apple Vision Pro and 100 images generated via an iPhone's "Spatial Camera" app. The corresponding mean opinion scores (MOSs) are collected under three viewing modes, including 2D display, 3D-window display, and 3D-immersive display. Furthermore, based on our database, we conduct a benchmark experiment and evaluate the performance of 22 state-of-the-art IQA models under three different viewing modes. We hope this research can facilitate future IQA research on egocentric spatial images. The database is available at https://github.com/IntMeGroup/ESIQA.

翻译：随着扩展现实（XR）技术的发展，头戴式拍摄与显示技术取得了显著进步并受到广泛关注。自我中心空间图像与视频正成为一种极具吸引力的立体XR内容形式。与传统二维图像不同，自我中心空间图像因其特殊的拍摄方式、处理手段及立体特性，给感知质量评估带来了挑战。然而，针对此类图像的相应图像质量评估研究目前仍较为缺乏。本文建立了自我中心空间图像质量评估数据库（ESIQAD），据我们所知，这是首个专用于自我中心空间图像的IQA数据库。我们的ESIQAD包含500幅自我中心空间图像，其中400幅使用Apple Vision Pro拍摄，100幅通过iPhone的“空间相机”应用生成。相应的平均意见分数（MOS）在三种观看模式下收集，包括二维显示、三维窗口显示和三维沉浸式显示。此外，基于本数据库，我们进行了基准实验，评估了22种先进IQA模型在三种不同观看模式下的性能。我们希望本研究能推动未来关于自我中心空间图像的IQA研究。数据库可通过 https://github.com/IntMeGroup/ESIQA 获取。