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Open AccessArticle

A Flexible Object-of-Interest Annotation Framework for Online Video Portals

Institute of Software Technology and Interactive Systems, Vienna University of Technology, Favoritenstrasse 9-11, Vienna A-1040, Austria
Future Internet 2012, 4(1), 179-215;
Received: 23 November 2011 / Revised: 2 February 2012 / Accepted: 20 February 2012 / Published: 22 February 2012
(This article belongs to the Special Issue Visual Information Retrieval)
In this work, we address the use of object recognition techniques to annotate what is shown where in online video collections. These annotations are suitable to retrieve specific video scenes for object related text queries which is not possible with the manually generated metadata that is used by current portals. We are not the first to present object annotations that are generated with content-based analysis methods. However, the proposed framework possesses some outstanding features that offer good prospects for its application in real video portals. Firstly, it can be easily used as background module in any video environment. Secondly, it is not based on a fixed analysis chain but on an extensive recognition infrastructure that can be used with all kinds of visual features, matching and machine learning techniques. New recognition approaches can be integrated into this infrastructure with low development costs and a configuration of the used recognition approaches can be performed even on a running system. Thus, this framework might also benefit from future advances in computer vision. Thirdly, we present an automatic selection approach to support the use of different recognition strategies for different objects. Last but not least, visual analysis can be performed efficiently on distributed, multi-processor environments and a database schema is presented to store the resulting video annotations as well as the off-line generated low-level features in a compact form. We achieve promising results in an annotation case study and the instance search task of the TRECVID 2011 challenge.
Keywords: video annotation; video sharing; object recognition video annotation; video sharing; object recognition
MDPI and ACS Style

Sorschag, R. A Flexible Object-of-Interest Annotation Framework for Online Video Portals. Future Internet 2012, 4, 179-215.

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