Abstract
Correct interpretation of the events occurring in video has a key role in the improvement of
video surveillance systems and the desired automatic decision making. Accurate analysis
of the context of the scenes in a video can contribute to the semantic understanding of the
video. In this paper, we present our research on context analysis within video sequences
focusing on fast automatic detection of sky and road. Regarding road detection, the
goal of the present study is to develop a motion-based context analysis to annotate roads
and to restrict the computationally heavy search for moving objects to the areas where
the motion is detected. Our sky detection approach is adopted from Zafarifar et al. [1].
To evaluate the results, the average Coverability Rate (CR) is used. Results of the
road detection algorithm are yielding a CR = 0.97 in a single highway video sequence.
Regarding sky detection, we illustrate that our algorithm performs well comparing with [2]
showing a CR of 0.98.
| Original language | English |
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| Title of host publication | Proceedings of the 33rd WIC Symposium on Information Theory in the Benelux joint with the 2nd WIC/IEEE SP Symposium on Information Theory and Signal Processing in the Benelux, 24-25 May 2012, Boekeloo, The Netherlands |
| Pages | 212-219 |
| Publication status | Published - 2012 |