Succeeding metadata based annotation scheme and visual tips for the automatic assessment of video aesthetic quality in car commercials

作者：

Highlights：

• Visual descriptors are used for the automatic assessment of aesthetics in car spots.

• 72.18% classification accuracy for 2 classes. Also significant results with up to 5.

• New video descriptors are demonstrated as indicative of viewer subjective perception.

• A metadata based clustering method is validated for the annotation of video corpora.

• 3 annotation strategies are tested according to how metadata are generated by viewers.

摘要

•Visual descriptors are used for the automatic assessment of aesthetics in car spots.•72.18% classification accuracy for 2 classes. Also significant results with up to 5.•New video descriptors are demonstrated as indicative of viewer subjective perception.•A metadata based clustering method is validated for the annotation of video corpora.•3 annotation strategies are tested according to how metadata are generated by viewers.

论文关键词：Automatic video annotation,Aesthetic quality assessment,Video sentiment analysis,Video metadata,YouTube

论文评审过程：Available online 8 August 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.07.033