Landmarking for Navigational Streaming of Stored High-Dimensional Media

نویسندگان

چکیده

Modern media data such as 360° videos and light field (LF) images are typically captured in much higher dimensions than the observers’ visual displays. To efficiently browse high-dimensional media, a navigational streaming model is considered: client navigates space by dictating navigation path to server, who response transmits corresponding pre-encoded units (MDU) one-by-one sequence. Assuming that MDU quality pre-chosen fixed, problem resides selecting storing redundant representations of MDUs at server order best trade off storage transmission costs, while enabling adequate user’s random access. We address this with landmark-based optimization framework. The divided into neighborhoods, each containing one landmark (a chosen MDU). neighborhood use associated predictor for inter-coding. Thus, any transition within same neighborhood, only inter-coded required when decoder buffer. It results lower cost enables optimize an structure, we employ tree-structured vector quantizer (TSVQ) first locations, then iteratively add P-MDUs refinements using fast branch-and-bound technique. Taking interactive LF viewport adaptive illustrative applications, I-, P- previously proposed merge frames intra- inter-code MDUs, show experimentally landmarked structures can noticeably reduce expected compared without landmarks.

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ژورنال

عنوان ژورنال: IEEE Transactions on Circuits and Systems for Video Technology

سال: 2022

ISSN: ['1051-8215', '1558-2205']

DOI: https://doi.org/10.1109/tcsvt.2022.3150780