baidut / s-prime

Code for the ISM 2015 paper "An Illumination-Robust Approach for Feature-Based Road Detection"

Overview | Installation | Setup | Acknowledgment | License

Overview

Code for the ISM 2015 paper "Illumination-Robust Approach for Feature-Based Road Detection" ( ieeexplore paper html pdf )

Citation

@INPROCEEDINGS{ying2015ism, 
author={Z. Ying and G. Li and G. Tan}, 
booktitle={2015 IEEE International Symposium on Multimedia (ISM)}, 
title={An Illumination-Robust Approach for Feature-Based Road Detection}, 
year={2015}, 
pages={278-281}, 
keywords={feature extraction;image colour analysis;intelligent transportation systems;cast shadows;feature-based method;grayscale image;illumination-related effects;input color image;intelligent vehicle systems;lane-marking detection;road boundary lines;road detection algorithms;Feature extraction;Gray-scale;Image color analysis;Image edge detection;Lighting;Roads;Transforms;image processing;intelligent vehicle systems;lane detection;road detection}, 
doi={10.1109/ISM.2015.46}, 
month={Dec},}

Installation

1. Download roma dataset from official website or baiduyun OpenVehicleVision/datasets/ROMA/roma.zip.
2. Download latest released code .

Setup

./add_to_path       % required libraries
./roma              % roma dataset
./roadDetection.m   % main algorithm
./demo.m

1. Open Matlab and cd your_path e.g. cd E:\Documents\MATLAB\s-prime
2. Add add_to_path to matlab path.
3. Run demo. (or demo method roma_dataset_path e.g. demo ours E:\Documents\MATLAB\s-prime\roma ), then the detection results will be displayed and be stored to subfolder .\result-*, after processing all the result, an evaluation report will be generated automatically in latex, see .\result-*\evaluation.tex

Acknowledgment

This project was supported by Shenzhen Peacock Plan (20130408-183003656), and by Science and Technology Planning Project of Guangdong Province, China (No. 2014B090910001).

License

Copyright (c) 2015-2016 Zhenqiang Ying

Licensed under the MIT license.

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