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Proceedings Paper

A novel approach to object detection in video using region-based motion diffusion
Author(s): Michael Hoynck; Michael Unger; Jens-Rainer Ohm
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Paper Abstract

Nowadays, the video coding standards for object based video coding and the tools for multimedia content description are available. Hence, we have powerful tools that can be used for content-based video coding, description, indexing and organization. In the past, it was difficult to extract higher level semantics, such as video objects, automatically. In this paper, we present a novel approach to moving object region detection. For this purpose, we developed a framework which applies bidirectional global motion estimation and compensation in order to identify potential foreground object regions. After spatial image segmentation, the results are assigned to image segments, and further diffused over the image region. This enables robust object region detection also in cases, where the investigated object does not move completely all the time. Finally, each image segment can be classified as being either situated in the foreground or in the background. Subsequent region merging delivers foreground object masks which can be used in order to define the region-of-attention for content based video coding, but also for contour based object classification.

Paper Details

Date Published: 25 October 2004
PDF: 12 pages
Proc. SPIE 5601, Internet Multimedia Management Systems V, (25 October 2004); doi: 10.1117/12.578517
Show Author Affiliations
Michael Hoynck, RWTH Aachen (Germany)
Michael Unger, RWTH Aachen (Germany)
Jens-Rainer Ohm, RWTH Aachen (Germany)


Published in SPIE Proceedings Vol. 5601:
Internet Multimedia Management Systems V
John R. Smith; Tong Zhang; Sethuraman Panchanathan, Editor(s)

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