PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Object flow: learning object displacement
C. Lalos, H. Grabner, Luc Van Gool and T. Varvarigou
In: 10th IEEE international workshop on visual surveillance - VS2010, 8 Nov 2010, Queenstown, New Zealand.

Abstract

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.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:7906
Deposited By:Luc Van Gool
Deposited On:17 March 2011