Road lane reconstruction using vision — based macro block spatial predictions

Vision — based road lane detection and reconstruction is a very common interest in the field of computer vision (CV). It has numerous application ranging from autonomous vehicle to driver assist and support systems technology. These researches are always focusing on both accuracy and complexity of the system's output; however, none of these uses Macro Block (MB) method. This paper introduces the characteristics of MB method used for spatial road lane detection and reconstruction subjected to different environment conditions; different MB size; and different function approximations.

[1]  Quoc Bao Truong,et al.  Lane boundaries detection algorithm using vector lane concept , 2008, 2008 10th International Conference on Control, Automation, Robotics and Vision.

[2]  Fangliang Chen,et al.  Detecting and tracking vehicles in traffic by unmanned aerial vehicles , 2016 .

[3]  Mohan M. Trivedi,et al.  Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation , 2006, IEEE Transactions on Intelligent Transportation Systems.

[4]  Xiangjing An,et al.  Multi-scale and Multi-orientation Local Feature Extraction for Lane Detection Using High-Level Information , 2011, 2011 Sixth International Conference on Image and Graphics.

[5]  Massimo Bertozzi,et al.  GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection , 1998, IEEE Trans. Image Process..

[6]  L. S. Bartolome,et al.  Vehicle parking inventory system utilizing image recognition through artificial neural networks , 2012, TENCON 2012 IEEE Region 10 Conference.

[7]  Elmer P. Dadios,et al.  Machine vision for traffic violation detection system through genetic algorithm , 2015, 2015 International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM).

[8]  Ian D. Reid,et al.  Stable multi-target tracking in real-time surveillance video , 2011, CVPR 2011.

[9]  Hanêne Ben-Abdallah,et al.  An Artificial Vision-Based Lane Detection Algorithm , 2009, 2009 2nd International Conference on Computer Science and its Applications.

[10]  Fuqiang Liu,et al.  A Vision Based Lane Detection and Tracking Algorithm in Automatic Drive , 2008, 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application.

[11]  Andrew Reed Bacha.  Line Detection and Lane Following for an Autonomous Mobile Robot , 2005 .

[12]  Dean A. Pomerleau,et al.  RALPH: rapidly adapting lateral position handler , 1995, Proceedings of the Intelligent Vehicles '95. Symposium.

[13]  Sergiu Nedevschi,et al.  Probabilistic Lane Tracking in Difficult Road Scenarios Using Stereovision , 2009, IEEE Transactions on Intelligent Transportation Systems.

[14]  Rama Chellappa,et al.  A Learning Approach Towards Detection and Tracking of Lane Markings , 2012, IEEE Transactions on Intelligent Transportation Systems.