Abstract
Currently, large areas are continuously monitored by camera networks, whereas an overall situation assessment within a reasonable time is a crucial requirement. In this paper, we propose our Virtual Top View (VTV) approach that provides a clear, concise and direct interpretation of on-field activities in real-time preserving the spatial relationship and, technically, employs planar homography to aggregate the Virtual Top View out of multiple, individual video streams. With an increasing number of cameras or size of the monitored area, the aggregation process slows down. Therefore, we develop acceleration methods (autogenerated warp maps) to achieve a real-time aggregation within large camera networks. Finally, we evaluate the performance and demonstrate our approach in an intra-logistics environment.
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Borstell, H., Pathan, S.S., Soffner, M., Richter, K. (2013). Virtual Top View: Towards Real-Time Agregation of Videos to Monitor Large Areas. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_68
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DOI: https://doi.org/10.1007/978-3-642-40246-3_68
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