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A Comparative Evaluation of Temporal Pooling Methods for Blind Video Quality Assessment

Citation Author(s):
Zhengzhong Tu, Chia-Ju Chen, Li-Heng Chen, Neil Birkbeck, Balu Adsumilli, Alan C. Bovik
Submitted by:
Zhengzhong Tu
Last updated:
2 November 2020 - 8:00pm
Document Type:
Presentation Slides
Document Year:
2020
Event:
Presenters Name:
Chia-Ju Chen
Categories:

Abstract 

Abstract: 

Many objective video quality assessment (VQA) algorithms include a key step of temporal pooling of frame-level quality scores. However, less attention has been paid to studying the relative efficiencies of different pooling methods on no-reference (blind) VQA. Here we conduct a large-scale comparative evaluation to assess the capabilities and limitations of multiple temporal pooling strategies on blind VQA of user-generated videos. The study yields insights and general guidance regarding the application and selection of temporal pooling models. In addition, we also propose an ensemble pooling model built on top of high-performing temporal pooling models. Our experimental results demonstrate the relative efficacies of the evaluated temporal pooling models, using several popular VQA algorithms evaluated on two recent largescale natural video quality databases. Conclusively, we also provide an empirical recipe for applying temporal pooling of frame-based quality predictions.

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Dataset Files

ICIP2020_PoolingVQA_Slides.pdf

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