Direct Estimation of Structure and Motion from Multiple Frames

This paper presents a method for the estimation of scene structure and camera motion from a sequence of images. This approach is fundamentally new. No computation of optical flow or feature correspondences is required. The method processes image sequences of arbitrary length and exploits the redundancy for a significant reduction in error over time. No assumptions are made about camera motion or surface structure. Both quantities are fully recovered. Our method combines the ``direct'''' motion vision approach with the theory of recursive estimation. Each step is illustrated and evaluated with results from real images.

[1]  William L. Brogan.  Applied Optimal Estimation (Arthur Gels, ed.) , 1977 .

[2]  Claude L. Fennema,et al.  Velocity determination in scenes containing several moving objects , 1979 .

[3]  H. C. Longuet-Higgins,et al.  The interpretation of a moving retinal image , 1980, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[4]  J. Roach,et al.  Determining the movement of objects from a sequence of images , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  W. Eric L. Grimson,et al.  From images to surfaces , 1981 .

[6]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Ellen C. Hildreth,et al.  Measurement of Visual Motion , 1984 .

[8]  P. Anandan,et al.  Computing Dense Displacement Fields With Confidence Measures In Scenes Containing Occlusion , 1985, Other Conferences.

[9]  Amar Mitiche,et al.  On Kineopsis and Computation of Structure and Motion , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Shahriar Negahdaripour,et al.  Direct passive navigation: Analytical solution for planes , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[11]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Andrew Blake,et al.  Visual Reconstruction , 1987, Deep Learning for EEG-Based Brain–Computer Interfaces.

[13]  Shahriar Negahdaripour,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence , 2004 .

[14]  Berthold K. P. Horn,et al.  COMPUTATIONALLY-EFFICIENT METHODS FO R RECOVERING TRANSLATIONAL MOTIO N , 1987 .

[15]  Robert C. Bolles,et al.  Epipolar-plane image analysis: a technique for analyzing motion sequences , 1987 .

[16]  Ernst D. Dickmanns.  4D-Szenenanalyse mit integralen raum-/zeitlichen Modellen , 1987, DAGM-Symposium.

[17]  R. Szeliski,et al.  Incremental estimation of dense depth maps from image sequences , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Shahriar Negahdaripour,et al.  A direct method for locating the focus of expansion , 1989, Comput. Vis. Graph. Image Process..

[19]  E. D. Dickmans,et al.  Subject-object discrimination in 4D dynamic scene interpretation for machine vision , 1989, [1989] Proceedings. Workshop on Visual Motion.

[20]  Joachim Heel.  Dynamic motion vision , 1990, Robotics Auton. Syst..