A video texture database for perceptual compression and quality assessment

Miltiadis Alexios Papadopoulos, Aaron Zhang, Dimitris Agrafiotis, David Bull

Research output: Contribution to conferenceConference Paperpeer-review

32 Citations (Scopus)


This paper presents a new publicly available video texture database (BVI Texture) that contains test sequences and subjective opinion scores. The database exhibits a wide range of static and dynamic textures together with some mixed content. Each sequence is indexed using various video feature descriptors that characterize its spatial activity, temporal activity, static texture content and dynamic texture content. Moreover, rate/distortion results for the new dataset are presented after compression using HEVC, alongside subjective quality evaluation data. The BVI texture database will provide utility in testing quality assessment metrics and emerging video compression methods, particularly those based on texture analysis and synthesis.
Original languageEnglish
Pages2781 - 2785
Number of pages5
Publication statusPublished - Dec 2015


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