Robust structure from motion estimation using inertial data

Journal of the Optical Society of America A: Optics and Image Science, and Vision

Volumn 18, Issue 12, 2001, Pages 2982-2997

  Qian, Gang ^a   Chellappa, Rama ^a   Zheng, Qinfen ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION; DATA REDUCTION; IMAGE ANALYSIS; KALMAN FILTERING; ROBUSTNESS (CONTROL SYSTEMS);

INERTIAL DATA ANALYSIS;

MOTION ESTIMATION;

EID: 0011980855     PISSN: 10847529     EISSN: 15208532     Source Type: Journal    
DOI: 10.1364/JOSAA.18.002982     Document Type: Article

References (28)

1. R. Tsai and T. Huang, “Estimating 3-D motion parameters of a rigid planar patch. 1,” IEEE Trans. Acoust. Speech Signal Process. ASP-29, 1147-1152 (1981).
2. T. J. Broida and R. Chellappa, “Estimation of object motion parameters from noisy image,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8, 90-99 (1986).
3. T. J. Broida, S. Chandrashekhar, and R. Chellappa, “Recur- sive estimation of 3-D kinematics and structure from a noisy monocular image sequence,” IEEE Trans. Aerosp. Electron. Syst. 26, 639-656 (1990).
4. T. Jebara, A. Azarbayejani, and A. Pentland, “3-D structure from 2D motion,” IEEE Signal Process. Mag. 16(3), 66-84 (1999).
5. J. Oliensis, “A critique of structure from motion algo- rithms,” Tech. Rep. (NEC Research Institute, Prince- ton, N.J., 2000), www.neci.nj.com/homepages/oliensis/
6. poleiccv. ps. C. Jerian and R. Jain, “Structure from motion: a critical
7. analysis of methods,” IEEE Trans. Syst. Man Cybern. 21, 572-588 (1991).
8. P. Narayanan, P. Rander, and T. Kanade, “Constructing virtual worlds using dense stereo,” in Proceedings of the 6th International Conference on Computer Vision (Narosa, New Delhi, 1998), pp. 3-10.
9. T. Vieville and O. Faugeras, “Computation of inertial infor- mation on a robot,” in Proceedings of the Fifth International Symposium on Robotics Research
10. H. Miura and S. Arimoto, eds. (MIT, Cambridge, Mass., 1989), pp. 57-65.
11. T. Vieville, Romann, B. Hotz, H. Mathieu, M. Buffa, L. Rob- ert, P. Facao, O. Faugeras, and J. Audren, “Autonomous navigation of a mobile robot using inertial and visual cues,” in Intelligent Robots and Systems
12. M. Kikode, T. Sato, and K. Tatsuno, eds. (Publisher unknown, Yokohama, 1993).
13. T. Mukai and N. Ohnishi, “The recovery of object shape and camera motion using a sensing system with a video camera and a gyro sensor,” in Proceedings of the 7th International Conference on Computer Vision (IEEE Computer Society, Los Alamitos, Calif., 1999), pp. 411-417.
14. S. Neill, “Synchronous data sampling system for image/data fusion,” in Proceedings of the 3rd Annual Fedlab Sym- posium (U.S. Army Research Laboratory, Adelphi, Md., 1999), pp. 107-109.
15. J. M. Ortolf, P. Zemany, W. J. Kaiser, M. J. Dong, K. G. Yung, R. Howe, and A. Seshia, “Microsensors for army ap- plications,” in Proceedings of the 2nd Annual Fedlab Sym- posium (U.S. Army Research Laboratory, Adelphi, Md., 1998), pp. 93-98.
16. A. Azarbayejani and A. Pentland, “Recursive estimation of motion, structure, and focal length,” IEEE Trans. Pattern Anal. Mach. Intell. 17, 562-575 (1995).
17. A. H. Jazwinski, Stochastic Processes and Filtering Theory (Academic, New York, 1970).
18. H. Poor, An Introduction to Signal Detection and Estimation (Springer-Verlag, New York, 1988).
19. G. Young and R. Chellappa, “Statistical analysis of inherent ambiguities in recovering 3-D motion from a noisy flow field,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 9951013 (1992).
20. T. Broida and R. Chellappa, “Performance bounds for esti- mating three-dimensional motion parameters from a se- quence of noisy images,” J. Opt. Soc. Am. A 6, 879-889 (1989).
21. Z. Zhang, “Determining the epipolar geometry and its un- certainty: a review,” Tech. Rep. No. 2927 (French National Institute for Research in Computer Science and Control, Paris, 1996).
22. R. Tsai and T. Huang, “Uniqueness and estimation of three- dimensional motion parameters of rigid objects with curved surfaces,”IEEE Trans. Pattern Anal. Mach. Intell. PAMI-6, 13-27 (1984).
23. G. Adiv, “Inherent ambiguities in recovering 3-D motion and structure from a noisy flow field,” IEEE Trans. Pattern Anal. Mach. Intell. 11, 477-489 (1989).
24. K. Daniilidis and H. Nagel, “The coupling of rotation and translation in motion estimation of planar surfaces,” in Proceedings of the 8th IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1993), pp. 188-193.
25. D. Lawton, “Processing translational motion sequences,” Comput. Vision Graph. Image Process. 22, 116-144 (1983).
26. G. Adiv, “Determining 3-D motion and structure from opti- cal flow generated by several moving objects,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-7, 384-401 (1985).
27. J. Oliensis, “A multi-frame structure-from-motion algo- rithm under perspective projection,” Int. J. Comput. Vision 34, 1-30 (1999).
28. C. Tomasi and J. Shi, “Good features to track,” in Proceedings of the 9th IEEE Computer Society Conference on Com- puter Vision and Pattern Recognition (IEEE Computer So- ciety, Los Alamitos, Calif., 1994), pp. 593-600.