Abstract
Discovering roles and their relationship is critical in movie content analysis. However, most conventional approaches ignore the correlations among roles or require rich metadata such as casts and scripts, which makes them not practical when little metadata is available, especially in the scenarios of IPTV and VOD systems. To solve this problem, we propose a new method to discover key roles and their relationship by treating a movie as a small community. We first segment a movie into a hierarchical structure (including scene, shot, and key-frame), and perform face detection and grouping on the detected key-frames. Based on such information, we then create a community by exploiting the key roles and their correlations in this movie. The discovered community provides a wide variety of applications. In particular, we present in this paper the automatic generation of video poster (with four different visualizations) based on the community, as well as preliminary experimental results.
This work was performed at Microsoft Research Asia.
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Wang, Y., Mei, T., Hua, XS. (2011). Community Discovery from Movie and Its Application to Poster Generation. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_11
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DOI: https://doi.org/10.1007/978-3-642-17832-0_11
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