Pre-fetching based on video analysis for interactive region-of-interest streaming of soccer sequences

We consider a video streaming system in which the user can interactively watch an arbitrary region of a high-spatial-resolution scene. Region-of-interest (RoI) prediction helps pre-fetch select slices of encoded video. The more accurate the RoI prediction the lower is the percentage of missing pixel...

Full description

Saved in:
Bibliographic Details
Published in2009 16th IEEE International Conference on Image Processing (ICIP) pp. 3061 - 3064
Main Authors Mavlankar, A., Girod, B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:We consider a video streaming system in which the user can interactively watch an arbitrary region of a high-spatial-resolution scene. Region-of-interest (RoI) prediction helps pre-fetch select slices of encoded video. The more accurate the RoI prediction the lower is the percentage of missing pixels. We compare different techniques for RoI prediction for streaming soccer sequences. Two techniques proposed in our earlier work are not domain-specific and can be applied to any type of content. Here we propose two techniques geared for soccer sequences that perform semantic video analysis. The goal of the paper is to find out whether domain-specific techniques can predict the client's RoI more accurately. Experiments indicate that for short prediction look-ahead there is little gain whereas for a long prediction look-ahead of 2 seconds the percentage of missing pixels can be reduced from 24% for the best general technique to 18% for the best domain-specific technique. This translates to a PSNR gain of around 1 dB for long prediction look-ahead. The percentage of missing pixels can be reduced further by spending additional bitrate for pre-fetching a margin around the predicted RoI.
ISBN:9781424456536
1424456533
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2009.5414201