Title :
Real-time estimation of drivable image area based on monocular vision
Author :
Miranda Neto, A. ; Correa Victorino, Alessandro ; Fantoni, I. ; Ferreira, J.V.
Author_Institution :
Autonomous Mobility Lab. (LMA), FEM/UNICAMP, Brazil
Abstract :
Camera-based estimation of drivable image areas is still in evolution. These systems have been developed for improved safety and convenience, without the need to adapt itself to the environment. Machine Vision is an important tool to identify the region that includes the road in images. Road detection is the major task of autonomous vehicle guidance. In this way, this work proposes a drivable region detection algorithm that generates the region of interest from a dynamic threshold search method and from a drag process (DP). Applying the DP to estimation of drivable image areas has not been done yet, making the concept unique. Our system was has been evaluated from real data obtained by intelligent platforms and tested in different types of image texture, which include occlusion case, obstacle detection and reactive navigation.
Keywords :
cameras; hidden feature removal; image texture; mobile robots; real-time systems; roads; robot vision; telerobotics; autonomous vehicle guidance; drag process; drivable region detection algorithm; image texture; machine vision; monocular vision-based drivable image area; obstacle detection; occlusion case; reactive navigation; real-time estimation; road images; threshold search method; Cameras; Image segmentation; Machine vision; Real-time systems; Roads; Sensors; Vehicles;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location :
Gold Coast, QLD
Print_ISBN :
978-1-4673-2754-1
DOI :
10.1109/IVS.2013.6629448