Color-based road detection in urban traffic scenes

By Yinghua He, Hong Wang, Bo Zhang. IEEE transactions on intelligent transportation systems (Print), 2004

395 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Robust Lane Detection From Continuous Driving Scenes Using Deep Neural Networks (2019, methodology): “In [26], color was also used for road lane extraction.”
Overview of Environment Perception for Intelligent Vehicles (2017, methodology): “This algorithm is composed of two modules: boundaries were estimated using the intensity image and road areas were detected using the full color image [40].”
A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios (2014, background): “He et al. [25] proposed two steps.”
Lane Detection With Moving Vehicles in the Traffic Scenes (2006, methodology): “According to [14], the boundary module and area module in their method takes 0.”
Shadow Resistant Road Segmentation from a Mobile Monocular System (2007, background): “Now, such segmentation can be augmented with road shape models like in [9,10] with the aim of estimating the not seen road in case of many vehicles in the scene.”