Title :
Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis
Author :
Sivaraman, Sayanan ; Trivedi, Mohan Manubhai
Author_Institution :
Lab. for Intell. & Safe Automobiles, Univ. of California San Diego, La Jolla, CA, USA
Abstract :
This paper provides a review of the literature in on-road vision-based vehicle detection, tracking, and behavior understanding. Over the past decade, vision-based surround perception has progressed from its infancy into maturity. We provide a survey of recent works in the literature, placing vision-based vehicle detection in the context of sensor-based on-road surround analysis. We detail advances in vehicle detection, discussing monocular, stereo vision, and active sensor-vision fusion for on-road vehicle detection. We discuss vision-based vehicle tracking in the monocular and stereo-vision domains, analyzing filtering, estimation, and dynamical models. We discuss the nascent branch of intelligent vehicles research concerned with utilizing spatiotemporal measurements, trajectories, and various features to characterize on-road behavior. We provide a discussion on the state of the art, detail common performance metrics and benchmarks, and provide perspective on future research directions in the field.
Keywords :
automated highways; behavioural sciences; computer vision; filtering theory; image fusion; object detection; object tracking; road vehicles; stereo image processing; active sensor-vision fusion; behavior understanding; dynamical models; filtering analysis; intelligent vehicle research; monocular vision domains; on-road behavior analysis; on-road vision-based vehicle detection; sensor-based on-road surround analysis; spatiotemporal measurements; stereo-vision domains; vision-based surround perception; vision-based vehicle tracking; Computer vision; Intelligent vehicles; Machine learning; Object detection; Object tracking; Computer vision; intelligent vehicles; machine learning; object detection; object tracking;
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2013.2266661