This paper presents a novel method for retrieving different instances of a region or object of interest in a video database.
We propose three dynamic region construction and matching algorithms aiming at obtaining the most similar instance of
the query model from each candidate image. The first two involve a greedy, dynamic region construction method. The
third is based on simulated annealing, and aims at determining a global optimum. An interactive selection mechanism
allows the user to select an object directly from the video and to start a query using as input this information in order to
access visually similar content. Experimental results show promising performances, with object detection rates of up to
81%.
This paper introduces a novel on-line video browsing and retrieval platform, so-called OVIDIUS (On-line VIDeo
Indexing Universal System). In contrast with traditional and commercial video retrieval platforms, where video content is
treated in a more or less monolithic manner (i.e. with global descriptions associated with the whole document), the
proposed approach makes it possible to browse and access video content in a finer, per-segment basis. The hierarchical
metadata structure exploits the ISO/MPEG-7 approach for structural description of video content, which provides a
multi-granular, hierarchical framework for heterogeneous metadata fusion.
The issues of content interaction and visualization, which are of highest relevance in both annotation and metadata
exploitation stages are also addressed. Our innovative approach makes it possible to quickly provide a comprehensive
overview of complex video documents with a minimal time and interaction effort. The developed approach shows all its
pertinence within a multi-terminal context and in particular for video access from mobile devices.
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