@inproceedings{526bdfd8c96347139b5939e56a1aee33,
title = "Segmentation through edge-linking: Segmentation for video-based driver assistance systems",
abstract = "This work aims to develop an image segmentation method to be used in automotive driver assistance svstems. In this context it is possible to incorporate a priori knovvledge from other sensors to ease the problem of local-izing objects and to improve the results. It is however desired to product accurate segmentations displaving good edge localization and to have real time capabilities. An edge-segment grouping method is presented to meetthese aims. Edges of varying strength aredetected initiallv. In various preprocessing steps edge-segments are formed. A sparse graph is generated from those using perceptual grouping phenomena. Closed contours are formed by solving the shortest path problem. Using test data fitting to the application domain, it is shown that the proposed method provides more accurate results than the vvell-knovn Gradient Vector Field Snakes.",
keywords = "Driver assistance, Edge linking, Object recognition, Segmentation",
author = "Andreas Laika and Adrian Taruttis and Walter Stechele",
year = "2009",
language = "English",
isbn = "9789898111685",
series = "IMAGAPP 2009 - Proceedings of the 1st International Conference on Computer Imaging Theory and Applications",
pages = "43--49",
booktitle = "IMAGAPP 2009 - Proceedings of the 1st International Conference on Computer Imaging Theory and Applications",
note = "1st International Conference on Computer Imaging Theory and Applications, IMAGAPP 2009 ; Conference date: 05-02-2009 Through 08-02-2009",
}