GOLD: A Framework for Developing Intelligent-Vehicle Vision Applications

Abstract

To develop real-time vision applications for use in highly dynamic environments, such as automotive traffic, researchers must gather large amounts of data from different sensors and systems at different rates. Software capable of real-time data acquisition, synchronization, logging, and - ultimately - data processing and visualization is fundamentally important to improving researcher efficiency. The general obstacle and lane detection framework supports different devices and makes it easy to add new system functionalities. GOLD can easily become the engine for many automotive applications, and it could work in other application domains as well.