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Volume: 33 | Article ID: art00016
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A Content-Based Viewport Prediction Model
Dario D. R. Morais
Lucas S. Althoff
Ravi Prakash
Marcelo M. Carvalho
Mylène C.Q. Farias
  DOI :  10.2352/ISSN.2470-1173.2021.9.IQSP-255  Published Online :  January 2021
Abstract

Viewport prediction technologies are often used by most popular adaptive 360-degree video streaming solutions. These solutions stream only the content considered as being more likely to be watched by the final user, with the goal of reducing the volume of network traffic without compromising the user’s Quality of Experience (QoE). In this paper, we propose the Most Viewed Cluster algorithm (MVC), which is a hybrid viewport prediction method. It estimates the user viewport using two types of information: (i) the path of moving objects in the scene and (ii) the viewing behavior of previous users. Preliminary results show that MVC yields good results for long-term predictions.

Journal Title : Electronic Imaging
Publisher Name : Society for Imaging Science and Technology
Publisher Location : IS&T 7003 Kilworth Lane Springfield, VA 22151 USA
Subject Areas :
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 DOI 10.2352/ISSN.2470-1173.2021.9.IQSP-255
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  Cite this article 

Dario D. R. Morais, Lucas S. Althoff, Ravi Prakash, Marcelo M. Carvalho, Mylène C.Q. Farias, "A Content-Based Viewport Prediction Model"  in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XVIII,  2021,  pp 255-1 - 255-8,  https://doi.org/10.2352/ISSN.2470-1173.2021.9.IQSP-255

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Copyright © Society for Imaging Science and Technology 2021
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane Springfield, VA 22151 USA
10.2352/ISSN.2470-1173.2021.9.IQSP-255
2470-1173(20210118)2021:9L.2551;1-
ei_24701173_v2021n9_Input/s22.xml
/ist/ei/2021/00002021/00000009/art00016
Articles
A Content-Based Viewport Prediction Model
MoraisDario D. R.
AlthoffLucas S.
PrakashRavi
CarvalhoMarcelo M.
FariasMylène C.Q.
18012021
2021
9
255-1
255-8
2021
Viewport prediction technologies are often used by most popular adaptive 360-degree video streaming solutions. These solutions stream only the content considered as being more likely to be watched by the final user, with the goal of reducing the volume of network traffic without compromising the user’s Quality of Experience (QoE). In this paper, we propose the Most Viewed Cluster algorithm (MVC), which is a hybrid viewport prediction method. It estimates the user viewport using two types of information: (i) the path of moving objects in the scene and (ii) the viewing behavior of previous users. Preliminary results show that MVC yields good results for long-term predictions.
viewport predictionobject tracking360-degree videoprefetchingclustering