Abstract
The phenomenal growth of World Wide Web has caused an easier and faster access to multimedia contents. The volume of available multimedia contents like Hindi movies’ music databases online has been exponentially increased. It results in dire need of automatic music retrieval from such databases. In recent years content-based music retrieval has been viewed as a potential solution to it. The ability of content based music retrieval is to automatically identify different characteristics of music data such as its genre. Unfortunately, the existing genre identifiers that are mostly tested on western music databases, has very low accuracy on Hindi movies’ music databases. Moreover, all the existing approaches of genre identification are based on music audio. In this paper, we propose a framework to automatically identify genre of a Hindi movie song using its video features. We used video shot duration and actor movement to classify the songs in pop, romantic, and tragic classes. We performed our experiments on 105 popular Hindi movies’ songs falling evenly in three proposed genres. An accuracy of 89.5% has been achieved that proves the effect of music video on its genre.
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Doudpota, S.M., Guha, S., Baber, J. (2012). Shot-Based Genre Identification in Musicals. In: Venugopal, K.R., Patnaik, L.M. (eds) Wireless Networks and Computational Intelligence. ICIP 2012. Communications in Computer and Information Science, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31686-9_15
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DOI: https://doi.org/10.1007/978-3-642-31686-9_15
Publisher Name: Springer, Berlin, Heidelberg
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