Estimating Drivable Collision-Free Space from Monocular Video

In this paper we propose a novel algorithm for estimating the drivable collision-free space for autonomous navigation of on-road and on-water vehicles. In contrast to previous approaches that use stereo cameras or LIDAR, we show a method to solve this problem using a single camera. Inspired by the success of many vision algorithms that employ dynamic programming for efficient inference, we reduce the free space estimation task to an inference problem on a 1D graph, where each node represents a column in the image and its label denotes a position that separates the free space from the obstacles. Our algorithm exploits several image and geometric features based on edges, color, and homography to define potential functions on the 1D graph, whose parameters are learned through structured SVM. We show promising results on the challenging KITTI dataset as well as video collected from boats.

[1]  W. F. Clocksin,et al.  Joint Optimization for Object Class Segmentation and Dense Stereo Reconstruction , 2011, International Journal of Computer Vision.

[2]  Luc Van Gool,et al.  3D City Modeling Using Cognitive Loops , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[3]  Pietro Perona,et al.  Fast Terrain Classification Using Variable-Length Representation for Autonomous Navigation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Alexei A. Efros,et al.  Automatic photo pop-up , 2005, ACM Trans. Graph..

[5]  Jan-Michael Frahm,et al.  3D Reconstruction Using an n-Layer Heightmap , 2010, DAGM-Symposium.

[6]  Ben Taskar,et al.  Max-Margin Markov Networks , 2003, NIPS.

[7]  Roland Siegwart,et al.  Appearance-Guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles , 2008, IEEE Transactions on Robotics.

[8]  Viii Supervisor.  Sonar-Based Real-World Mapping and Navigation , 2001 .

[9]  Luc Van Gool,et al.  Stixels estimation without depth map computation , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[10]  David Silver,et al.  Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain , 2010, Int. J. Robotics Res..

[11]  Andreas Geiger,et al.  Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Andrew J. Davison,et al.  DTAM: Dense tracking and mapping in real-time , 2011, 2011 International Conference on Computer Vision.

[13]  Thomas Hofmann,et al.  Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..

[14]  Roland Siegwart,et al.  Introduction to Autonomous Mobile Robots, Second Edition , 2011, Intelligent robotics and autonomous agents.

[15]  Alexei A. Efros,et al.  IM2GPS: estimating geographic information from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Olga Veksler,et al.  Tiered scene labeling with dynamic programming , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Olivier Stasse,et al.  MonoSLAM: Real-Time Single Camera SLAM , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Roland Siegwart,et al.  Introduction to Autonomous Mobile Robots , 2004 .

[19]  G. Klein,et al.  Parallel Tracking and Mapping for Small AR Workspaces , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[20]  Jean-Philippe Tarel,et al.  Real time obstacle detection in stereovision on non flat road geometry through "v-disparity" representation , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[21]  Uwe Franke,et al.  Fast stereo based object detection for stop&go traffic , 1996, Proceedings of Conference on Intelligent Vehicles.

[22]  Heiko Hirschmüller,et al.  Stereo Processing by Semiglobal Matching and Mutual Information , 2008, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Yann LeCun,et al.  Learning long‐range vision for autonomous off‐road driving , 2009, J. Field Robotics.

[24]  James M. Rehg,et al.  Traversability classification using unsupervised on-line visual learning for outdoor robot navigation , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[25]  Sebastian Thrun,et al.  Self-supervised Monocular Road Detection in Desert Terrain , 2006, Robotics: Science and Systems.

[26]  Isabelle Fantoni,et al.  Real-time estimation of drivable image area based on monocular vision , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[27]  Uwe Franke,et al.  The Stixel World - A Compact Medium Level Representation of the 3D-World , 2009, DAGM-Symposium.

[28]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[29]  Sanjiv Singh,et al.  The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, George Air Force Base, Victorville, California, USA , 2009, The DARPA Urban Challenge.

[30]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[31]  Sebastian Scherer,et al.  River mapping from a flying robot: state estimation, river detection, and obstacle mapping , 2012, Auton. Robots.

[32]  D. Scharstein,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001).

[33]  Ashutosh Saxena,et al.  High speed obstacle avoidance using monocular vision and reinforcement learning , 2005, ICML.

[34]  Bharath Sankaran,et al.  Self-supervised segmentation of river scenes , 2011, 2011 IEEE International Conference on Robotics and Automation.

[35]  Rudolf Mester,et al.  Free Space Computation Using Stochastic Occupancy Grids and Dynamic Programming , 2008 .

[36]  David Nistér,et al.  An efficient solution to the five-point relative pose problem , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Andreas Geiger,et al.  Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.