Impact of automatic region-of-interest coding on perceived quality in mobile video

Abstract

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic regionof-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: (1) automatic ROI by analyzing the visual contents automatically, and (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROIbased video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

Video Quality Evaluation for Tile-Based Spatial Adaptation

“…Previous work demonstrates that a proper rate allocation strategy might lead to substantial (albeit content-dependent [12]) gains in terms of perceived visual quality. In [9] these gains were shown to be more important at low bitrates; however, their results were found on mobile video, and it is not clear how this conclusion extends to high-resolution content.…”

“…Coding video with spatially varying quality has been largely studied in the past decades. Examples include sprite coding [3], MPEG-4 Visual Objects [4], [5] and other more recent ROI-based bit allocation schemes for H.264/AVC and H.265/HEVC [6], [7], [8], [9], [10], [11]. In most cases, ROI-based allocation targets specific applications scenarios, e.g., assigning higher quality to faces in teleconferencing [8], [10].…”

Assessment of the Evolution in Quality for Xamarin Android Multimedia Applications

“…The tests should take into consideration the in-app permissions, the device permissions and the behavior of the application regarding the access on the external memory. Furthermore, if applications need the streaming of multimedia such as game playing [6] or video and sound [7] downloading from Cloud, a certain level of quality and connectivity should be continuously provided. Before any sync on libraries such as Google Photos or OneDrive, the captured images should be managed by the MediaStore Class.…”