@misc {pub2610,
	title = {Workshop on Benchmarking Road Terrain and Lane Detection Algorithms for In-Vehicle Applications},
	author = {Jannik Fritsch},
	year = {2014},
	month = {June},
	abstract = {Detecting the road area and ego-lane ahead of a vehicle is central to modern driver assistance systems. While lane-detection on well-marked roads is already available in modern vehicles, finding the boundaries of unmarked or weakly marked roads and lanes as they appear in inner-city and rural environments remains an unsolved problem due to the high variability in scene layout and illumination conditions, amongst others. While recent years have witnessed great interest in this subject, to date no commonly agreed upon benchmark exists, rendering a fair comparison amongst methods difficult. The target of this workshop is to bring together researchers active in the field in order to enable a better comparison of approaches. By encouraging submissions operating on public benchmarks (e.g., KITTI-ROAD, http://www.cvlibs.net/datasets/kitti/eval_road.php) the workshop aims to foster research progress in road terrain and lane detection algorithms for application in real vehicles driving on arbitrary non-highway roads.

Relevant topics of interest include, but are not limited to:

- Road segmentation approaches operating on KITTI-ROAD,
- Ego lane detection approaches operating on KITTI-ROAD,
- New evaluation measures for comparing road terrain/lane detection algorithms,
- Comparison of available road terrain/lane detection benchmarks.
- New benchmarks for road terrain/lane detection algorithms.
},
	publisher = {IEEE},
	booktitle = {Dearborn, Michigan, USA}
}