Recursive estimation of motion and a scene model with a two-camera system of divergent view

Pattern Recognition

Volumn 43, Issue 6, 2010, Pages 2265-2280

  Kim, Jae Hean ^a   Jin Chung, Myung ^b   Tae Choi, Byung ^a  

^a Electronics and Telecommunications Research Institute (ETRI)   (South Korea)

^b Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Extended Kalman filter; Field of view; Motion; Scene reconstruction; Stereo; Stereo correspondence; Structure from motion

Indexed keywords

FIELD OF VIEWS; MOTION SCENES; STEREO; STEREO CORRESPONDENCES; STRUCTURE FROM MOTION;

ESTIMATION; EXTENDED KALMAN FILTERS; MOTION ESTIMATION; POSITION CONTROL; REPAIR;

CAMERAS;

EID: 76749140338     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2009.12.015     Document Type: Article

References (47)

1. Wolf P.R. Elements of Photogrammetry (1983), McGraw-Hill, New York
2. Tomasi C., and Kanade T. Shape and motion from image streams under orthography: a factorization method. Int. J. Comput. Vision 9 2 (1992) 137-154
3. Szeliski R., and Kang S.B. Recovering 3D shape and motion from image streams using nonlinear least square. J. Visual Commun. Image Representation 5 1 (1994) 10-28
4. Pollefeys M. Visual modeling with a hand-held camera. Int. J. Comput. Vision 59 3 (2004) 207-232
5. Broida T., Chandrashekhar S., and Chellapa R. Recursive 3-D motion estimation from a monocular image sequence. IEEE Trans. Aerosp. Electron. Syst. 26 4 (1990) 639-656
6. Azarbayejani A., and Pentland A.P. Recursive estimation of motion, structure, and focal length. IEEE Trans. Pattern Anal. Mach. Intell. 17 6 (1995) 562-575
7. Chiuso A., Favaro P., Jin H., and Soatto S. Structure from motion causally integrated over time. IEEE Trans. Pattern Anal. Mach. Intell. 24 4 (2002) 523-535
8. Jin H., Favaro P., and Soatto S. A semi-direct approach to structure from motion. Visual Comput. 19 6 (2003) 377-394
9. Calway A. Recursive estimation of 3D motion and surface structure from local affine flow parameters. IEEE Trans. Pattern Anal. Mach. Intell. 27 4 (2005) 562-574
10. Fermüller C., and Aloimonos Y. Observability of 3D motion. Int. J. Comput. Vision 37 1 (2000) 43-63
11. P. Chang, M. Hebert, Omni-directional structure from motion, in: Proceedings of the IEEE Workshop on Omnidirectional Vision, 2000, pp. 127-133.
12. D. Strelow, J. Mishler, S. Singh, H. Herman, Extending shape-from-motion to noncentral omnidirectional cameras, in: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, Hawaii, USA, 2001, pp. 2086-2092.
13. J.-H. Kim, M.J. Chung, Map generation from unknown planar motion using omni-directional vision, in: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, Hawaii, USA, 2001, pp. 889-894.
14. Bunschoten R., and Kröse B. Robust scene reconstruction from an omnidirectional vision system. IEEE Trans. Robot. Autom. 19 2 (2003) 351-357
15. P. Corke, D. Strelow, S. Singh, Omnidirectional visual odometry for a planetary rover, in: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, 2004, pp. 4007-4012.
16. Kang S.B., and Szeliski R. 3-D scene data recovery using omnidirectional multibaseline stereo. Int. J. Comput. Vision 25 2 (1997) 167-183
17. F. Dellaert, A.W. Stroupe, Linear 2D localization and mapping for single and multiple robot scenarios, in: Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, USA, 2002, pp. 688-694.
18. Davison A.J., and Murray D.W. Simultaneous localization and map-building using active vision. IEEE Trans. Pattern Anal. Mach. Intell. 24 7 (2002) 865-880
19. A.-T. Tsao, Y.-P. Hung, C.-S. Fuh, Y.-S. Chen, Ego-motion estimation using optical flow fields observed from multiple cameras, in: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, 1997, pp. 457-462.
20. M. Etoh, T. Aoki, K. Hata, Estimation of structure and motion parameters for a roaming robot that scans the space, in: Proceedings of the IEEE International Conference on Computer Vision, 1999, pp. 579-584.
21. T. Sato, S. Ikeda, N. Yokoya, Extrinsic camera parameter recovery from multiple image sequences captured by an omni-directional multi-camera system, in: Proceedings of the European Conference on Computer Vision, 2004, pp. 326-340.
22. Baker P., Ogale A.S., and Fermüller C. The argus eye: a new imaging system designed to facilitate robotic tasks of motion. IEEE Robot. Autom. Mag. 11 4 (2004) 31-38
23. Pless R. Camera cluster in motion: motion estimation for generalized camera designs. IEEE Robot. Autom. Mag. 11 4 (2004) 39-44
24. Point Grey Research Inc., Ladybug2, 2005. URL 〈http://www.ptgrey.com/products/ladybug2/index.html〉.
25. H. Li, R. Hartley, J. Kim, A linear approach to motion estimation using generalized camera models, in: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, USA, 2008.
26. Dissanayake M.W.M.G., Newman P., Clark S., Durrant-Whyte H.F., and Csorba M. A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans. Robot. Autom. 17 3 (2001) 229-241
27. Davison A.J., Reid I.D., Molton N.D., and Stasse O. MonoSLAM: real-time single camera SLAM. IEEE Trans. Pattern Anal. Mach. Intell. 29 6 (2007) 1052-1067
28. Thurun S., Fox D., and Burgard W. A probabilistic approach to concurrent mapping and localization for mobile robots. Mach. Learn. Autonomous Robots 31 (1998) 29-53
29. Pupilli M., and Calway A. Real-time camera tracking using a particle filter. Proceedings of the British Machine Vision Conference (2005), Oxford, England 519-528
30. Kim J.-H., and Chung M.J. Absolute motion and structure from stereo image sequences without stereo correspondence and analysis of degenerate cases. Pattern Recognition 39 9 (2006) 1649-1661
31. B. Williams, G. Klein, I. Reid, Real-time SLAM relocalisation, in: Proceedings of the IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, 2007.
32. Civiera J., Davison A.J., and Montiel J.M.M. Inverse depth parametrization for monocular SLAM. IEEE Trans. Robot. 24 5 (2008) 932-945
33. Olson C.F., Matthies L.H., Schoppers M., and Maimone M.W. Rover navigation using stereo ego-motion. Robot. Autonomous Syst. 43 (2003) 215-229
34. I.-K. Jung, S. Lacroix, High resolution terrain mapping using low attitude aerial stereo imagery, in: Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, 2003, pp. 946-951.
35. D. Nistér, O. Naroditsky, J. Bergen, Visula odometry, in: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Washington, DC, USA, 2004, pp. 652-659.
36. Chui C.K., and Chen G. Kalman Filtering with Real-Time Application (1990), Springer, Berlin
37. J. Shi, C. Tomasi, Good features to track, in: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Seattle, 1994, pp. 593-600.
38. T. Tommasini, A. Fusiello, E. Trucco, V. Roberto, Making good features track better, in: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, 1998, pp. 178-183.
39. R. Hartley, In defence of the 8-point algorithm, in: Proceedings of the International Conference on Computer Vision, Sendai, Japan, 1995, pp. 1064-1070.
40. Faugeras O., and Lustman F. Motion and structure from motion in a piecewise planar environment. Int. J. Pattern Recognition Artif. Intell. 2 3 (1988) 485-508
41. Dhond U.R., and Aggarwal J.K. Structure from stereo-a review. IEEE Trans. Syst. Man Cybern. 19 6 (1989) 1489-1510
42. Faugeras O. Three-dimensional Computer Vision (1993), The MIT Press, Cambridge, MA
43. M. Lourakis, A. Argyros, The design and implementation of a generic sparse bundle adjustment software package based on the Levenberg-Marquardt algorithm, Technical Report 340, Institute of Computer Science-FORTH, Heraklion, Crete, Greece, August 2004, available from 〈http://www.ics.forth.gr/lourakis/sba〉.
44. Guivant J.E., and Nebot E.M. Solving computational and memory requirements of feature-based simultaneous localization and mapping algorithms. IEEE Trans. Robot. Autom. 19 4 (2003) 749-755
45. Neira J., and Tardós J.D. Data association in stochastic mapping using the joint compatibility test. IEEE Trans. Robot. Autom. 17 6 (2001) 890-897
46. Se S., Loew D.G., and Little J.J. Vision-based global localization and mapping for mobile robots. IEEE Trans. Robot. 21 3 (2005) 364-375
47. Evolution Robotics Inc., vSLAM, 2005. URL 〈http://www.evolution.com/core/navigation/vslam.masn〉.