tailieunhanh - Towards Computational Models of Visual Aesthetic Appeal of Consumer Videos

The appeal of horn shapes is not difficult to understand in the field. One quickly learns to appreciate the variety of trained and untrained shapes in a forest of horns in the cattle camp. Both the symmetrical and the asymmetrical curving shapes of Nilotic cattle horns have great visual appeal, especially when they are seen moving through space as the cattle move their heads, and when the arcs the horns make in the air are exaggerated by the swinging movements of the tassels. Fagg (. 1973) has drawn attention to the frequent use of exponential curves in African art:. | Towards Computational Models of Visual Aesthetic Appeal of Consumer Videos Anush K. Moorthy Pere Obrador and Nuria Oliver Telefonica Research Barcelona Spain. Abstract. 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 1 Introduction In today s digital world we face the challenge of developing efficient multimedia data management tools that enable users to organize and search multimedia content from growing repositories of digital media. Increasing storage capabilities at low prices combined with pervasive devices to capture digital images and videos enable the generation and archival of unprecedented amounts of personal multimedia content. For eg. as of May 2009 about 20 hours of video footage - most of it user-generated - were uploaded on the popular video sharing site YouTube every minute 1 . In addition the number of user-generated video creators is expected to grow in the US by 77 from 2008 to 2013 2 . Text query-based image and video search approaches rely heavily on the similarity between the input textual query and the textual metadata . tags comments etc. that has previously been added to the content by users. Relevance is certainly critical to the satisfaction of users with their search results yet not sufficient. For example any visitor of YouTube will attest to the fact that most relevant search results today include a