Abstract
The past few years have seen a dramatic request for semantic video analysis. Object based interpretation in real-time imposes increased challenges on resource management to maintain sufficient quality of service, and requires careful design of the system architecture. This paper focuses on the role of context for system performance in a multi-stage object detection process. We extract context from simple features to determine regions of interest, provide an innovative method to identify the object’s topology from local object features, and we outline the concept for a correspondingly structured system architecture. Performance implications are analysed with reference to the application of logo detection in sport broadcasts and provide evidence for the crucial improvements achieved from context information.
This work is funded by the European Commission’s IST project DETECT under grant number IST-2001-32157.
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Paletta, L., Greindl, C. (2003). Context Based Object Detection from Video. In: Crowley, J.L., Piater, J.H., Vincze, M., Paletta, L. (eds) Computer Vision Systems. ICVS 2003. Lecture Notes in Computer Science, vol 2626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36592-3_48
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DOI: https://doi.org/10.1007/3-540-36592-3_48
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