  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.
