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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Object Flow: Learning Object Displacement
verfasst von : Constantinos Lalos, Helmut Grabner, Luc Van Gool, Theodora Varvarigou
Erschienen in: Computer Vision – ACCV 2010 Workshops
Verlag: Springer Berlin Heidelberg
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Modelling the dynamic behaviour of moving objects is one of the basic tasks in computer vision. In this paper, we introduce the
Object Flow
, for estimating both the displacement and the direction of an object-of-interest. Compared to the detection and tracking techniques, our approach obtains the object displacement directly similar to optical flow, while ignoring other irrelevant movements in the scene. Hence,
Object Flow
has the ability to continuously focus on a specific object and calculate its motion field. The resulting motion representation is useful for a variety of visual applications (e.g., scene description, object tracking, action recognition) and it cannot be directly obtained using the existing methods.