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Object Tracking and Segmentation in a Closed Loop

Summary: Object Tracking and Segmentation in
a Closed Loop
Konstantinos E. Papoutsakis and Antonis A. Argyros
Institute of Computer Science, FORTH
Computer Science Department, University of Crete
Abstract. We introduce a new method for integrated tracking and seg-
mentation of a single non-rigid object in an monocular video, captured
by a possibly moving camera. A closed-loop interaction between EM-like
color-histogram-based tracking and Random Walker-based image seg-
mentation is proposed, which results in reduced tracking drifts and in
fine object segmentation. More specifically, pixel-wise spatial and color
image cues are fused using Bayesian inference to guide object segmenta-
tion. The spatial properties and the appearance of the segmented objects
are exploited to initialize the tracking algorithm in the next step, closing
the loop between tracking and segmentation. As confirmed by experi-
mental results on a variety of image sequences, the proposed approach
efficiently tracks and segments previously unseen objects of varying ap-


Source: Argyros, Antonis - Foundation of Research and Technology, Hellas & Department of Computer Science, University of Crete


Collections: Computer Technologies and Information Sciences