Towards Computational Models of Visual Aesthetic Appeal of Consumer Videos

In this paper, we tackle the problem of characterizing the aesthetic appeal of consumer videos and automatically classifying them into high or low aesthetic appeal. First, we conduct a controlled user study to collect ratings on the aesthetic value of 160 consumer videos. Next, we propose and evaluate a set of low level features that are combined in a hierarchical way in order to model the aesthetic appeal of consumer videos. After selecting the 7 most discriminative features, we successfully classify aesthetically appealing vs. aesthetically unappealing videos with a 73% classification accuracy using a support vector machine. Key words: Video aesthetics, video quality, subjective assessment

• Type: Conference
• Year: 2010
• Where: ECCV
• Keywords: Aesthetic Appeal, Computer Vision, Consumer Videos, ECCV 2010, Low Aesthetic Appeal