Abstract
This paper tackles the issue of retrieving different instances of an object of interest within a given video document or in a video database. The principle consists in considering a semi-global image representation based on an over-segmentation of image frames. An aggregation mechanism is then applied in order to group a set of sub-regions into an object similar to the query, under a global similarity criterion. Two different strategies are proposed. The first one involves a greedy, dynamic region construction method. The second is based on simulated annealing, and aims at determining a global optimum. Experimental results show promising performances, with object detection rates of up to 79%.
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Bursuc, A., Zaharia, T., Prêteux, F. (2012). Retrieval of Multiple Instances of Objects in Videos. In: Schoeffmann, K., Merialdo, B., Hauptmann, A.G., Ngo, CW., Andreopoulos, Y., Breiteneder, C. (eds) Advances in Multimedia Modeling. MMM 2012. Lecture Notes in Computer Science, vol 7131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27355-1_34
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DOI: https://doi.org/10.1007/978-3-642-27355-1_34
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