Omnidirectional Visual Place Recognition using Rotation Invariant Sequence Matching

In this work we develop a visual place recognition system for omnidirectional panoramic images that makes use of their full 360 degree circumferential angle of view. The system builds on our previous variant of the sequence SLAM algorithm to include panoramic image rotation alignment for improved image similarity scoring, and bi-directional query and database sequence matching within a Hidden Markov Model (HMM) framework for robust place recognition. Three rotation alignment methods are explored including image pixel registration, and both image cross correlation and zero phase alignment in the spherical Fourier domain. All alignment methods operate using low-resolution images for computational efficiency. Experiments using an outdoor panoramic image dataset demonstrate improved precision recall performance using rotation alignment and bi-directional sequence matching. In particular, place recognition is possible in scenarios where a robot traverses a previous path in the opposite direction.

[1]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[2]  Winston Churchill,et al.  The New College Vision and Laser Data Set , 2009, Int. J. Robotics Res..

[3]  S. Shankar Sastry,et al.  Radon-based structure from motion without correspondences , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[4]  Andrew J. Viterbi,et al.  Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.

[5]  Shree K. Nayar,et al.  Catadioptric omnidirectional camera , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  T. Chan,et al.  Shape Registration with Spherical Cross Correlation , 2008 .

[7]  S. Nayar,et al.  Catadioptric Image Formation , 1997 .

[8]  Michael Milford,et al.  Vision-based place recognition: how low can you go? , 2013, Int. J. Robotics Res..

[9]  Kim M. Dalton,et al.  Encoding Cortical Surface by Spherical Harmonics , 2008 .

[10]  Peter I. Corke,et al.  Scale-Invariant Features on the Sphere , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[11]  Kostas Daniilidis,et al.  Spherical Correlation of Visual Representations for 3D Model Retrieval , 2009, International Journal of Computer Vision.

[12]  Peter I. Corke,et al.  Wide-angle Visual Feature Matching for Outdoor Localization , 2010, Int. J. Robotics Res..

[13]  Kostas Daniilidis,et al.  Rotation estimation from spherical images , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[14]  Brett Browning,et al.  Visual place recognition using HMM sequence matching , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Kostas Daniilidis,et al.  A Unifying Theory for Central Panoramic Systems and Practical Applications , 2000, ECCV.

[16]  Gordon Wyeth,et al.  SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights , 2012, 2012 IEEE International Conference on Robotics and Automation.

[17]  Paul Newman,et al.  Appearance-only SLAM at large scale with FAB-MAP 2.0 , 2011, Int. J. Robotics Res..

[18]  João Pedro Barreto,et al.  sRD-SIFT: Keypoint Detection and Matching in Images With Radial Distortion , 2012, IEEE Transactions on Robotics.

[19]  Thomas Bülow.  Multiscale Image Processing on the Sphere , 2002, DAGM-Symposium.

[20]  Paul Newman,et al.  Detecting Loop Closure with Scene Sequences , 2007, International Journal of Computer Vision.

[21]  T. Bulow.  Spherical diffusion for 3D surface smoothing , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Takeo Kanade,et al.  Visual topometric localization , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[23]  Brett Browning,et al.  Orientation only loop-closing with closed-form trajectory bending , 2012, 2012 IEEE International Conference on Robotics and Automation.

[24]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[25]  Andrew Zisserman,et al.  Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[26]  Václav Hlavác,et al.  Zero Phase Representation of Panoramic Images for Image Vased Localization , 1999, CAIP.

[27]  Kostas Daniilidis,et al.  Correspondence-free Structure from Motion , 2007, International Journal of Computer Vision.

[28]  Christopher Geyer,et al.  Equivalence of catadioptric projections and mappings of the sphere , 2000, Proceedings IEEE Workshop on Omnidirectional Vision (Cat. No.PR00704).

[29]  Kostas Daniilidis,et al.  Rotation recovery from spherical images without correspondences , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  D. Healy,et al.  Computing Fourier Transforms and Convolutions on the 2-Sphere , 1994 .

[31]  Harmonics Book,et al.  Geometric Applications Of Fourier Series And Spherical Harmonics , 2016 .

[32]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[33]  Kostas Daniilidis,et al.  Catadioptric Projective Geometry , 2001, International Journal of Computer Vision.

[34]  Shree K. Nayar,et al.  A Theory of Single-Viewpoint Catadioptric Image Formation , 1999, International Journal of Computer Vision.

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

[36]  Wolfram Burgard,et al.  G2o: A general framework for graph optimization , 2011, 2011 IEEE International Conference on Robotics and Automation.

[37]  Paul Newman,et al.  FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance , 2008, Int. J. Robotics Res..