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Issue No.01 - January/February (2008 vol.23)
pp: 69-71
Luca Bombini , VisLab, Università di Parma
Alberto Broggi , VisLab, Università di Parma
Paolo Zani , VisLab, Università di Parma
Massimo Bertozzi , VisLab, Università di Parma
Paolo Grisleri , VisLab, Università di Parma
Paolo Medici , VisLab, Università di Parma
ABSTRACT
To develop real-time vision applications for use in highly dynamic environments, such as transportation, researchers must gather large amounts of data coming from different sensors and systems at different rates. The Artificial Vision and Intelligent System Laboratory (VisLab) has been developing the GOLD (General Obstacle and Lane Detection) framework for more than 10 years to meet these requirements. It provides software that can perform data acquisition, synchronization, logging, processing, and visualization in real time. It's an efficient software layer that offers an engine for many automotive applications but could serve in many other application domains as well.
INDEX TERMS
collision avoidance, computer vision, software frameworks
CITATION
Luca Bombini, Alberto Broggi, Paolo Zani, Massimo Bertozzi, Paolo Grisleri, Paolo Medici, "GOLD: A Framework for Developing Intelligent-Vehicle Vision Applications", IEEE Intelligent Systems, vol.23, no. 1, pp. 69-71, January/February 2008, doi:10.1109/MIS.2008.6
REFERENCES
1. M. Bertozzi and A. Broggi, "GOLD: A Parallel Real-Time Stereo Vision System for Generic Obstacle and Lane Detection," IEEE Trans. Image Processing, vol. 7, no. 1, 1998, pp. 62–81.
2. A. Broggi et al., Automatic Vehicle Guidance: The Experience of the ARGO Autonomous Vehicle, World Scientific, 1999.
3. A. Broggi et al., "The Single Frame Stereo Vision System for Reliable Obstacle Detection Used during the 2005 DARPAGrand Challenge on TerraMax," Proc. IEEE Int'l Conf. Intelligent Transportation Systems (ITSC 06) IEEE Press, 2006, pp. 745–752.
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