Optical flow based plane detection for mobile robot navigation

Dominant plane detection is an essential task for an autonomous navigation of mobile robots equipped with a vision system, as we assume that robots move on the dominant plane. In this paper, based on optical flow, the image motions of points which located in a plane were described by planar flow. After the parameters of planar flow are estimated, the distance error of image points can be used for detecting the plane region from monocular image sequence. The proposed method includes three steps. First, the robust optical flow is estimated between two consecutive images from the image sequence. Then a geometry constraint provided by planar flow is applied to detect the plane regions in optical flow. And finally, some iterative procedures can be used for improving the results. Compared with the feature point based method which sometimes is invalid because of the lacking of texture, the optical flow based method can detect the ground plane even if there are not much more image features in the plane region. Some experiments with outdoor images have been conducted.

[1]  Andrew Blake,et al.  Quantitative planar region detection , 2004, International Journal of Computer Vision.

[2]  Boubakeur Boufama,et al.  Homography-based plane identification and matching , 2008, 2008 15th IEEE International Conference on Image Processing.

[3]  Bill Triggs,et al.  Autocalibration from Planar Scenes , 1998, ECCV.

[4]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[5]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[6]  Henrik I. Christensen,et al.  Multiple Plane Segmentation Using Optical Flow , 2002, BMVC.

[7]  Olivier Faugeras,et al.  Motion and Structure from Motion in a piecewise Planar Environment , 1988, Int. J. Pattern Recognit. Artif. Intell..

[8]  Manolis I. A. Lourakis,et al.  Detecting Planes In An Uncalibrated Image Pair , 2002, BMVC.

[9]  Michael J. Black,et al.  The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields , 1996, Comput. Vis. Image Underst..

[10]  Christoph Schnörr,et al.  A robust and convergent iterative approach for determining the dominant plane from two views without correspondence and calibration , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Zoltan Kato,et al.  Recovering planar homographies between 2D shapes , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[12]  Masayuki Inaba,et al.  Plane segment finder: algorithm, implementation and applications , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[13]  Roberto Cipolla,et al.  Automatic 3D Modelling of Architecture , 2000, BMVC.

[14]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[15]  Andrew Zisserman,et al.  Automatic reconstruction of piecewise planar models from multiple views , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[16]  Hao Wu,et al.  Motion Estimation for a Mobile Robot Based on Real-Time Stereo Vision System , 2009, 2009 2nd International Congress on Image and Signal Processing.