SoundsLike: movies soundtrack browsing and labeling based on relevance feedback and gamification

Abstract

Movies and games are amongst the biggest sources of entertainment, in individual and social contexts. Increasingly, movies and videos are becoming accessible as enormous collections over the Internet, in social media and interactive TV, demanding for new and more powerful ways to search, browse and view them, that benefit from video content-based analysis and classification techniques. Game elements, in turn, can help in this often challenging process, e.g. in the audio, to obtain user feedback to improve the efficacy of classification, while maintaining or improving the entertaining quality of the user experience. In this paper, we present and discuss SoundsLike, a gamification approach to engage users in movies soundtrack labeling, based on relevance feedback and integrated in MovieClouds, an interactive web application designed to access, explore and visualize movies based on the information conveyed in the different tracks or perspectives of its content, especially audio and subtitles where most of the semantics is conveyed, and with a special focus on the emotional dimensions expressed in the movies or felt by the viewers.