Autocalibration from Planar Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Obstacle avoidance and navigation in the real world by a seeing robot rover
Obstacle avoidance and navigation in the real world by a seeing robot rover
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Visual map-less navigation based on homographies
Journal of Robotic Systems
A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Two years of Visual Odometry on the Mars Exploration Rovers: Field Reports
Journal of Field Robotics - Special Issue on Space Robotics
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Flyphone: Visual Self-Localisation Using a Mobile Phone as Onboard Image Processor on a Quadrocopter
Journal of Intelligent and Robotic Systems
Closing the loop in appearance-guided omnidirectional visual odometry by using vocabulary trees
Robotics and Autonomous Systems
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This paper describes an algorithm for visually computing the ego-motion of a vehicle relative to the road under the assumption of planar motion. The algorithm uses only images taken by a single omnidirectional camera mounted on the roof of the vehicle. The front ends of the system are two different trackers. The first one is a homography-based tracker that detects and matches robust scale invariant features that most likely belong to the ground plane. The second one uses an appearance based approach and gives high resolution estimates of the rotation of the vehicle. This 2D pose estimation method has been successfully applied to videos from an automotive platform. We give an example of camera trajectory estimated purely from omnidirectional images over a distance of 400 meters. For performance evaluation, the estimated path is superimposed onto an aerial image. In the end, we use image mosaicing to obtain a textured 2D reconstruction of the estimated path.