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Aishy Amera Eric Duboisb aINRS-Telecommunications; Montreal, Qc; H5A 1K6 Canada


Aishy Amera Eric Duboisb
aINRS-Telecommunications; Montreal, Qc; H5A 1K6 Canada
bUniversity of Ottawa; Ottawa, On; K1N 6N5 Canada
Video is increasingly used in various advanced applications. Many of these applications require common video represen-
tations that should be oriented towards how people describe video content. In this paper we first discuss the background
of high-level video representations. We then introduce a computational framework for high-level video representation that
evolves towards how people describe video content. Our framework represents a video shot in terms of its moving objects
and their related semantic features such as events and other high-level motion features. To achieve higher applicability,
content should be extracted independently of the type and the context of the input video. Our representation system,
implemented on 6371 images with multi-object occlusion and artifacts, produces stable results in real-time. This is due
to the adaptation to noise, the compensation of estimation errors at the various processing levels, and the division of the
processing system into simple but effective tasks.
Video is becoming integrated in various personal and professional applications such as entertainment, education, tele-
medicine, databases, security applications and even low-bandwidth wireless applications. Providing means for fast, au-
tomated, and effective techniques to represent video based on its high-level content, such as objects and meanings, are
important topics of research.߿ In a surveillance application, for instance, object extraction is necessary to classify


Source: Amer, Aishy - Department of Electrical and Computer Engineering, Concordia University


Collections: Engineering