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  • 1989
  • Issue No. 5 - May
  • Abstract - The Precision of 3-D Parameters in Correspondence-Based Techniques: The Case of Uniform Translational Motion in a Rigid Environment
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The Precision of 3-D Parameters in Correspondence-Based Techniques: The Case of Uniform Translational Motion in a Rigid Environment
May 1989 (vol. 11 no. 5)
pp. 523-528
ASCII Text
x 
 
M.A. Snyder, "The Precision of 3-D Parameters in Correspondence-Based Techniques: The Case of Uniform Translational Motion in a Rigid Environment," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 5, pp. 523-528, May, 1989.
 
 
BibTex
x
 
@article{ 10.1109/34.24784,
author = {M.A. Snyder},
title = {The Precision of 3-D Parameters in Correspondence-Based Techniques: The Case of Uniform Translational Motion in a Rigid Environment},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {11},
number = {5},
issn = {0162-8828},
year = {1989},
pages = {523-528},
doi = {http://doi.ieeecomputersociety.org/10.1109/34.24784},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - The Precision of 3-D Parameters in Correspondence-Based Techniques: The Case of Uniform Translational Motion in a Rigid Environment
IS - 5
SN - 0162-8828
SP523
EP528
EPD - 523-528
A1 - M.A. Snyder,
PY - 1989
KW - picture processing; pattern recognition; 3D parameters precision; correspondence-based techniques; uniform translational motion; rigid environment; uncertainty-analysis; first-order-error-based motion algorithms; search region; pattern recognition; picture processing
VL - 11
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 

A general method of calculating the precision of environmental parameters which differs from conventional methods by finding analytical results, and which does so using only information in the image is discussed. This method called uncertainty-analysis, is applied to the case of first-order-error-based motion algorithms for determining environmental depth by matching corresponding points between two or more frames of a dynamic image sequence. How to calculate the uncertainty of in predicted values for the depth is shown, as well as how to calculate the search region for further instances of the point in subsequent frames, based only on information present in the image. The analysis is applied to a real image sequence with good results.

[1] G. Adiv, "Interpreting optical flow," Ph.D. dissertation, Dep. Comput. Inform. Sci., Univ. Massachusetts, Amherst, MA, Sept. 1985.
[2] S. Bharwani, E. Riseman, and A. Hanson, "Refinement of environmental depth maps over multiple frames," inDARPA I. U. Workshop Proc., Dec. 1985.
[3] S. D. Blostein and T. S. Huang, "Quantization errors in stereo triangulation," inProc. First Int. Conf. Comput. Vision, London, England, June 1987.
[4] H. F. Durrant-Whyte, "Integration, coordination, and control of multi-sensor robot systems," Dep. Comput. Inform. Sci., Univ. Pennsylvania, Aug. 1986.
[5] J.-Q. Fang and T. S. Huang, "Some experiments on estimating the 3-D motion parameters of a rigid body from two consecutive image frames,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, pp. 545-554, Sept. 1984.
[6] O. D. Faugeras, N. Ayache, B. Faverjon, and F. Lutsman, "Building visual maps by combining noisy stereo measurements," inProc. IEEE Conf. Robotics Automat.pp. 1433-1438, 1987.
[7] D. B. Gennery, "Modeling the environment of an exploring vehicle by means of stereo vision," Ph.D. dissertation, Stanford Univ., Stanford, CA, Stanford Artificial Intell. Lab. Memo 339, 1980.
[8] J.K. Kearny, W.B. Thompson, and D.L. Boley, "Optical flow estimation: An error analysis of gradient-based methods with local optimization,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-9, pp. 229-244, Mar. 1987.
[9] H. C. Longuet-Higgins and K. Prazdny, "The interpretation of a moving retinal image,"Proc. Roy. Soc. London, vol. B208, pp. 385- 397, 1980.
[10] L. Matthies and S. Shafer, "Error modelling in stereo navigation," Dep. Comput. Sci., Carnegie-Mellon Univ., Tech. Rep. CMU-CS- 86-140, 1986.
[11] H. P. Moravec, "Obstacle avoidance and navigation in the real world by a seeing robot rover," Ph.D. dissertation, Stanford Univ, Stanford, CA, Sept. 1980.
[12] M. A. Snyder, "The accufacy of 3-D parameters in correspondence-based techniques," Dep. Comput. Inform. Sci., Univ. Massachusetts, Amherst, Tech. Rep. 86-28, June 1986.
[13] M. A. Snyder, "On the computation of depth in motion and stereo," Dep. Comput. Inform. Sci., Univ. Massachusetts, Amherst, Tech. Rep. in preparation.
[14] R. Y. Tsai qnd T. S. Huang, "Uniqueness and estimation of 3-D motion parameters of rigid objects with curved surfaces,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, pp. 13-26, Jan. 1984.
[15] A. M. Waxman,et al., "Image processing for visual navigation of a roadway," Univ. Maryland, CAR Tech. Rep. 138, 1985.
[16] A. M. Waxman, "A visual navigation system for the autonomous land vehicle," Univ. Maryland, CAR Tech. Rep. 139, July 1985.

Index Terms:
picture processing; pattern recognition; 3D parameters precision; correspondence-based techniques; uniform translational motion; rigid environment; uncertainty-analysis; first-order-error-based motion algorithms; search region; pattern recognition; picture processing
Citation:
M.A. Snyder, "The Precision of 3-D Parameters in Correspondence-Based Techniques: The Case of Uniform Translational Motion in a Rigid Environment," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 5, pp. 523-528, May 1989, doi:10.1109/34.24784
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