Automating the construction of scene classifiers for content-based video retrieval

Israël, Menno and Broek van den, Egon L. and Putten van der, Peter (2004) Automating the construction of scene classifiers for content-based video retrieval. In: Fifth International Workshop on Multimedia Data Mining, MDM/KDD 2004, 22 August 2004, Seattle, WA, USA.

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Abstract:	This paper introduces a real time automatic scene classifier within content-based video retrieval. In our envisioned approach end users like documentalists, not image processing experts, build classifiers interactively, by simply indicating positive examples of a scene. Classification consists of a two stage procedure. First, small image fragments called patches are classified. Second, frequency vectors of these patch classifications are fed into a second classifier for global scene classification (e.g., city, portraits, or countryside). The first stage classifiers can be seen as a set of highly specialized, learned feature detectors, as an alternative to letting an image processing expert determine features a priori. We present results for experiments on a variety of patch and image classes. The scene classifier has been used successfully within television archives and for Internet porn filtering.
Item Type:	Conference or Workshop Item
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Human Media Interaction (HMI)
Link to this item:	http://purl.utwente.nl/publications/79285
Official URL:	http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.3296&rep=rep1&type=pdf
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