Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Fast segmentation of range images into planar regions by scan line grouping
Machine Vision and Applications
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Minimal Projective Reconstruction Including Missing Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Industrial Robot Navigation and Obstacle Avoidance Employing Fuzzy Logic
Journal of Intelligent and Robotic Systems
Using EM to Learn 3D Models of Indoor Environments with Mobile Robots
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Direct Obstacle Detection and Motion from Spatio-Temporal Derivatives
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Improved Temporal Correspondences in Stereo-Vision by RANSAC
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Robust Statistical Estimation and Segmentation of Multiple Subspaces
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Using Extended EM to Segment Planar Structures in 3D
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Planar Structure Based Registration of Multiple Range Images
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Robotics and Autonomous Systems
A RANSAC-based approach to model fitting and its application to finding cylinders in range data
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Three-dimensional mapping with time-of-flight cameras
Journal of Field Robotics - Three-Dimensional Mapping, Part 2
Accurate 3D ground plane estimation from a single image
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Image-based exploration obstacle avoidance for mobile robot
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Generalized velocity obstacles
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Incremental disparity space image computation for automotive applications
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A local obstacle avoidance method for mobile robots in partially known environment
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Three-dimensional point cloud plane segmentation in both structured and unstructured environments
Robotics and Autonomous Systems
International Journal of Computational Vision and Robotics
Hi-index | 0.00 |
A fundamental problem in autonomous vehicle navigation is the identification of obstacle free space in cluttered and unstructured environments. Features such as walls, people, furniture, doors and stairs, etc are potential hazards. The approach taken in this paper is motivated by the recent development on infra-red time-of-flight cameras that provide video frame rate low resolution depth maps. We propose to exploit the temporal information content provided by the high refresh rate of such cameras to overcome the limitations due to low spatial resolution and high depth uncertainty and aim to provide robust and accurate estimates of planar surfaces in the environment. These surfaces' estimates are then used to provide statistical tests to identify obstacles and dangers in the environment. Classical 3D spatial RANSAC is extended to 4D spatio-temporal RANSAC by developing spatio-temporal models of planar surfaces that incorporate a linear motion model as well as linear environment features. A 4D-vector product is used for hypotheses generation from data that is randomly sampled across both spatial and temporal variations. The algorithm is fully posed in the spatio-temporal representation and there is no need to correlate points or hypothesis between temporal images. The proposed algorithm is computationally fast and robust for estimation of planar surfaces in general and the ground plane in particular. There are potential applications in mobile robotics, autonomous vehicular navigation, and automotive safety systems. The claims of the paper are supported by experimental results obtained from real video data for a time-of-flight range sensor mounted on an automobile navigating in an undercover parking lot.