- Chunzhao Guo, Toyota Central R&D Labs., Inc., Japan (firstname.lastname@example.org)
- José M. Álvarez, NICTA, Australia (email@example.com)
- Jannik Fritsch, Honda Research Institute Europe, Germany (firstname.lastname@example.org)
- Andreas Geiger, Max Planck Institute for Intelligent Systems, Germany (email@example.com)
- Jannik Fritsch, Introduction of KITTI-ROAD for Benchmarking Road Detection Algorithms (KeyNote).
- Guo, Fritsch and Alvarez, Towards co-evolution of road / lane detection and benchmarking (Open Discussion)
- Giovani Barnardes Vitor, Alessandro Correa Victorino and Janito Vaqueiro Ferreira, Comprehensive Performance Analysis of Road Detection Algorithms Using the Common Urban Kitti-Road Benchmark.
- Inna Stainvas and Yosi Buda, Performance Detection for Curb Detection Problem.
- Bihao Wang, Vincent Fremont and Sergio Alberto Rodriguez Florez, Color-Based Road Detection and its Evaluation on the KITTI Road Benchmark.
- Patrick Shinzato, Denis Wolf and Christoph Stiller, Road Terrain Detection: Avoiding Common Obstacle Detection Assumptions using Sensor Fusion.
- Xiao Hu, Sergio Alberto Rodriguez Florez and Alexander Gepperth, A Multi-Modal System for Road Detection and Segmentation. Download video demo.
- Volker Patricio Schomerus, Dennis Rosebrock and Friedrich M. Wahl, Camera-based Lane Border Detection in Arbitrarily Structured Environments.
Description of the workshop
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.
Important Dates & Submissions
- Electronic submission of the workshop papers is due by February 22th, 2014 at http://its.papercept.net . Submission code of the workshop is “5guea”
- Workshop paper is limited to a total of six pages including references. A maximum of two supplementary pages is permitted at an extra charge
- Peer-reviewed workshop papers will be included in the Conference Proceedings
Presentations without submitting a full paper
- Authors intending to present research progress on road detection at the workshop without submitting a full paper are invited to submit an extended abstract
- The extended abstract is limited to 1-2 pages of A4 size (including figures), and should be sent to the organizers via email before March 31st, 2014
- The extended abstract must be clearly reflect the contents of the paper, and accompanied by the following information: Title of paper; Name of author(s); Affiliation(s); Abstract; Corresponding author (Name, Affiliation, E-mail address)
- The Organizing Committee will review the extended abstract. Accepted papers will be presented in an oral presentation at the workshop.
- Extended abstract will not be included in the Conference Proceedings; however, they will be distributed to attendees in electronic format