Unity3Dbased app for 360VR subjective quality assessment with customizable questionnaires This document describes an interactive virtual reality tool for subjective assessment designed under the scope of ITUT Study Group 12 and the Video Quality Experts Group in the development of the future ITUT Recommendation P.360VR for the subjective assessment of 360 videos using HeadMounted Displays (HMDs). The tool has been designed under the Unity3D engine to be used on multiple HMDs. Furthermore, it can be configured for a variety of custom or predefined questions while the video sequence is played andor after its ending. The head tracking is also registered in degrees. The voting method is gazebased using joysticks keys for confirmation.

Quality Assessment of Stereoscopic 360degree Images from Multiviewports Objective quality assessment of stereoscopic panoramic images becomes a challenging problem owing to the rapid growth of 360degree contents. Different from traditional 2D image quality assessment (IQA), more complex aspects are involved in 3D omnidirectional IQA, especially unlimited field of view (FoV) and extra depth perception, which brings difficulty to evaluate the quality of experience (QoE) of 3D omnidirectional images. In this paper, we propose a multiviewport based fullreference stereo 360 IQA model. Due to the freely changeable viewports when browsing in the headmounted display, our proposed approach processes the image inside FoV rather than the projected one such as equirectangular projection (ERP). In addition, since overall QoE depends on both image quality and depth perception, we utilize the features estimated by the difference map between left and right views which can reflect disparity. The depth perception features along with binocular image qualities are employed to further predict the overall QoE of 3D 360 images. The experimental results on our public Stereoscopic OmnidirectionaL Image quality assessment Database (SOLID) show that the proposed method achieves a significant improvement over some wellknown IQA metrics and can accurately reflect the overall QoE of perceived images.