A time-varying subjective quality model for mobile streaming videos with stalling events

Deepti Ghadiyaram; Janice Pan; Alan C. Bovik

doi:10.1117/12.2188882

22 September 2015 A time-varying subjective quality model for mobile streaming videos with stalling events

Deepti Ghadiyaram, Janice Pan, Alan C. Bovik

Proceedings Volume 9599, Applications of Digital Image Processing XXXVIII; 959911 (2015) https://doi.org/10.1117/12.2188882
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

Citation Download Citation

Deepti Ghadiyaram, Janice Pan, and Alan C. Bovik "A time-varying subjective quality model for mobile streaming videos with stalling events", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959911 (22 September 2015); https://doi.org/10.1117/12.2188882

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available