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Object detection and segmentation on a hierarchical region-based image representation

Author
Vilaplana, V.; Marques, F.; Leon, M.; Gasull, A.
Type of activity
Presentation of work at congresses
Name of edition
2010 IEEE International Conference on Image Processing
Date of publication
2010
Book of congress proceedings
Proceedings of the IEEE International Conference on Image Processing
First page
3393
Last page
3396
Repository
http://hdl.handle.net/2117/11435 Open in new window
Abstract
In this paper we present a general framework for object detection and segmentation. Using a bottom-up unsupervised merging algorithm, a region-based hierarchy that represents the image at different resolution levels is created. Next, top-down, object class knowledge is used to select and combine regions from the hierarchy, in order to define the exact object shape. We illustrate the usefulness of the approach with four different object classes: sky, caption text, traffic signs and faces.
Citation
Vilaplana, V. [et al.]. Object detection and segmentation on a hierarchical region-based image representation. A: IEEE International Conference on Image Processing. "2010 IEEE International Conference on Image Processing". Hong Kong: 2010, p. 3393-3396.
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

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