Real-time monocular visual odometry for on-road vehicles with 1-point RANSAC

— This paper presents a system capable of recovering the trajectory of a vehicle from the video input of a single camera at a very high frame-rate. The overall frame-rate is limited only by the feature extraction process, as the outlier removal and the motion estimation steps take less than 1 millisecond with a normal laptop computer. The algorithm relies on a novel way of removing the outliers of the feature matching process. We show that by exploiting the nonholonomic constraints of wheeled vehicles it is possible to use a restrictive motion model which allows us to parameterize the motion with only 1 feature correspondence. Using a single feature correspondence for motion estimation is the lowest model parameterization possible and results in the most efficient algorithms for removing outliers. Here we present two methods for outlier removal. One based on RANSAC and the other one based on histogram voting. We demonstrate the approach using an omnidirectional camera placed on a ve...

• Type: Conference
• Year: 2009
• Where: ICRA
• Authors: Davide Scaramuzza, Friedrich Fraundorfer, Roland Siegwart
• Keywords: Feature Correspondence, ICRA 2009, Motion Estimation, Outlier Removal, Robotics