Title :
Enhancing Vehicular Safety in Adverse Weather Using Computer Vision Analysis
Author :
Che-Tsung Lin ; Yu-Chen Lin ; Long-Tai Chen ; Yuan-Fang Wang
Author_Institution :
Mech. & Syst. Res. Labs., Ind. Technol. Res. Inst., Hsinchu, Taiwan
Abstract :
The goal of the project is to design intelligent and robust image-processing and augmented-reality algorithms for driver assistance and enhanced vehicular safety. In particular, the focuses were two-fold: (1) realizing the abilities to identify and localize in a vehicle´´s on-board video the sweeping windshield wipers during raining days and (2) designing and implementing an in-painting technique to remove the image of the windshield wipers and replace it with the corresponding pixels (not blocked by the wipers) from an adjacent video frame.
Keywords :
augmented reality; computer vision; driver information systems; object recognition; road safety; video signal processing; adverse weather; augmented-reality algorithms; computer vision analysis; driver assistance; in-painting technique; intelligent image-processing; raining days; robust image-processing; vehicle on-board video; vehicular safety enhancement; video frame; windshield wiper image removal; windshield wipers; Automotive components; Image color analysis; Roads; Shape; Training; Vectors; Vehicles;
Conference_Titel :
Vehicular Technology Conference (VTC Fall), 2014 IEEE 80th
Conference_Location :
Vancouver, BC
DOI :
10.1109/VTCFall.2014.6965965