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Automatic actors detection in musicals

机译:音乐剧中的演员自动检测

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摘要

Bollywood movies have become an important part of South Asian culture. Video musical pieces are integral parts of these movies. The growing ease of hosting multimedia contents online is resulting in a huge number of movie video songs available online. A common user usually likes to search a particular music piece, based on different criteria e.g. genre of a video song, or on-screen actor performing on a video song. Such information, in current implementation, is attached manually as a textual caption with the video songs. This textual caption with a video song is highly unreliable, especially when a video song is to be uploaded by an ordinary user, which is usually the case with online video songs. In this paper, we present an automatic approach of detecting the actors vocalizing a video song, who are usually the stars of the movie. Our approach is based on detecting actors faces from different parts of a video song and clustering the faces based on faces similarity. We tested the proposed actors detector on 30 video songs, belonging to different genres. An overall accuracy of 83.34% and 80% has been achieved on first and second main actors, respectively.
机译:宝莱坞电影已经成为南亚文化的重要组成部分。视频音乐作品是这些电影不可或缺的部分。在线托管多媒体内容的便捷性日益提高,导致在线提供了大量的电影视频歌曲。普通用户通常喜欢根据不同的标准(例如,视频歌曲的类型,或在视频歌曲上表演的屏幕演员。在当前的实现方式中,此类信息作为视频歌曲的文本标题手动附加。带有视频歌曲的文本标题非常不可靠,尤其是当视频歌曲要由普通用户上传时,在线视频歌曲通常就是这种情况。在本文中,我们提出了一种自动检测发声视频歌曲的演员的自动方法,这些演员通常是电影中的明星。我们的方法是基于检测视频歌曲不同部分中的演员面孔,并基于面孔相似度对面孔进行聚类。我们对30种不同类型的视频歌曲测试了拟议的演员检测器。第一和第二主要演员的整体准确率分别达到83.34%和80%。

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