Video shot classification with concept detection

Zhong Ji; Yuting Su

doi:10.1117/12.749160

15 November 2007 Video shot classification with concept detection

Zhong Ji, Yuting Su

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678816 (2007) https://doi.org/10.1117/12.749160
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

It is a challenging work to classify video shots into a predefined genre set according to their semantic contents, which is helpful to video indexing, summarization and retrieval. This research proposes a novel shot classification algorithm with concept detection for news video programs. Six semantic shot types are studied and categorized: Anchorperson, Monologue, Reporter, Commercial, Still image and Miscellaneous, in which anchorperson shots are detected by clustering methods, reporter and monologue shots are distinguished by Conditional Random Fields (CRFs), and the last three categories are picked out by rule-based methods. Multimodality features are employed, such as visual, audio, face, temporal and contextual features. The experimental results show its effectiveness and achieve a high average accuracy of 96.5%.

Citation Download Citation

Zhong Ji and Yuting Su "Video shot classification with concept detection", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678816 (15 November 2007); https://doi.org/10.1117/12.749160

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KEYWORDS

Video

Semantic video

Facial recognition systems

Classification systems

Visualization

Detection and tracking algorithms

Chromium

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