부산대학교 도서관

As video gameplay recording and streaming is becoming very popular on the Internet, there is an increasing need for automatic classification solutions to help service providers with indexing the huge amount of content and users with finding relevant content. The automatic classification of gameplay videos into specific genres is not a trivial task due to their high content diversity. This paper address the problem of classifying video gameplay recordings into different genres by using mid-level video representation based on the BossaNova descriptor. The paper also proposes a public dataset called GameGenre containing 700 gameplay videos groped into 7 genres. The results from experimental testing show up to 89% classification accuracy when the gameplay videos are described by BossaNova descriptor using BinBoost as low-level image descriptor.