Attention-driven monocular scene reconstruction for obstacle detection, robot navigation and map building

Authors:
E. Einhorn;Ch. Schröter;H. M. Gross
Affiliations:
Neuroinformatics and Cognitive Robotics Lab, Ilmenau University of Technology, Germany and MetraLabs GmbH, Germany;Neuroinformatics and Cognitive Robotics Lab, Ilmenau University of Technology, Germany;Neuroinformatics and Cognitive Robotics Lab, Ilmenau University of Technology, Germany
Venue:
Robotics and Autonomous Systems
Year:
2011

Citing 16
Cited 1

Using Occupancy Grids for Mobile Robot Perception and Navigation

Computer
Real-Time Correlation-Based Stereo Vision with Reduced Border Errors

International Journal of Computer Vision
A Multiple-Baseline Stereo

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision

Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
A Fast Recursive 3D Model Reconstruction Algorithm for Multimedia Applications

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Active Search for Real-Time Vision

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
MonoSLAM: Real-Time Single Camera SLAM

IEEE Transactions on Pattern Analysis and Machine Intelligence
Obstacle detection with a Photonic Mixing Device-camera in autonomous vehicles

International Journal of Intelligent Systems Technologies and Applications
Active Matching

ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Stereo vision for obstacle detection: a graph-based approach

GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Realtime depth estimation and obstacle detection from monocular video

DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Machine learning for high-speed corner detection

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Attentional Landmarks and Active Gaze Control for Visual SLAM

IEEE Transactions on Robotics
Inverse Depth Parametrization for Monocular SLAM

IEEE Transactions on Robotics
Real-time dense stereo for intelligent vehicles

IEEE Transactions on Intelligent Transportation Systems

OctoMap: an efficient probabilistic 3D mapping framework based on octrees

Autonomous Robots

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a feature-based approach for monocular scene reconstruction based on Extended Kalman Filters (EKF). Our method processes a sequence of images taken by a single camera mounted frontally on a mobile robot. Using a combination of various techniques, we are able to produce a precise reconstruction that is free from outliers and can therefore be used for reliable obstacle detection and 3D map building. Furthermore, we present an attention-driven method that focuses the feature selection to image areas where the obstacle situation is unclear and where a more detailed scene reconstruction is necessary. In extensive real-world field tests we show that the presented approach is able to detect obstacles that are not seen by other sensors, such as laser range finders. Furthermore, we show that visual obstacle detection combined with a laser range finder can increase the detection rate of obstacles considerably, allowing the autonomous use of mobile robots in complex public and home environments.