Structure from stereo vision using unsynchronized cameras for simultaneous localization and mapping

This paper presents a system for automatic reconstruction of 3D structure using two unsynchronized cameras. Three images are acquired sequentially from the left, right, and again from the left camera. A virtual image from the left camera synchronized with the right image is created by interpolating matching points of interest (SIFT features) in the two left images. Both geometric and probabilistic criteria are used to select the correct set of matching features amongst the three views. In an indoor environment, the method typically results in 3D structure with approximately 200 feature points, with a median 3D accuracy of 1.6 cm when the average depth is 3 m and the robot has moved 1-2 cm between each image acquisition.

[1]  Yaron Caspi,et al.  A step towards sequence-to-sequence alignment , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[2]  Ian D. Reid,et al.  Goal-directed Video Metrology , 1996, ECCV.

[3]  Dean Brown,et al.  Decentering distortion of lenses , 1966 .

[4]  Hai Tao,et al.  Dynamic depth recovery from unsynchronized video streams , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[5]  SchmidCordelia,et al.  A Performance Evaluation of Local Descriptors , 2005 .

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

[7]  Marcus Svedman,et al.  3-D Structure from Stereo Vision using Unsynchronized Cameras , 2005 .

[8]  Lior Wolf,et al.  Correspondence-free Synchronization and Reconstruction in a Non-rigid Scene , 2004 .

[9]  G. Wahba.  Spline models for observational data , 1990 .

[10]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  N. Karlsson,et al.  The vSLAM Algorithm for Navigation in Natural Environments , 2005 .

[13]  Yaron Caspi,et al.  Alignment of non-overlapping sequences , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[14]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[15]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[16]  Paolo Pirjanian,et al.  The vSLAM Algorithm for Robust Localization and Mapping , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[17]  Wojciech Chojnacki,et al.  A voting scheme for estimating the synchrony of moving-camera videos , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[18]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .