Abstract
Standard optical flow methods for motion or disparity estimation use a brightness constancy constraint equation (BCCE). This BCCE either handles a moving camera imaging a non-moving scene or a fixed camera imaging a moving scene. In this paper a BCCE is developed that can handle instantaneous motion of the camera on a 2D plane normal to the viewing direction and motion of the imaged scene. From the thus acquired up to 5 dimensional data set 3D object motion, 3D surface element position, and -normals can be estimated simultaneously. Experiments using 1d or 2d camera grids and a weighted total least squares (TLS) estimation scheme demonstrate performance in terms of systematic error and noise stability, and show technical implications.
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References
Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of optical flow techniques. IJCV 12(1), 43–77 (1994)
Bergen, J.R., Burt, P.J., Hingorani, R., Peleg, S.: A three-frame algorithm for estimating two-component image motion. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(9), 886–895 (1992)
Bigün, J., Granlund, G.H.: Optimal orientation detection of linear symmetry. In: ICCV, pp. 433–438 (1987)
Black, M., Fleet, D., Yacoob, Y.: Robustly estimating changes in image appearence. CVIU 7(1), 8–31 (2000)
Bruhn, A., Weickert, J., Schnörr, C.: Combining the advantages of local and global optic flow methods. In: Van Gool, L. (ed.) DAGM 2002. LNCS, vol. 2449, pp. 454–462. Springer, Heidelberg (2002)
Carceroni, R., Kutulakos, K.: Multi-view 3d shape and motion recovery on the spatio-temporal curve manifold. In: ICCV (1), pp. 520–527 (1999)
Jr. Denney, T.S., Prince, J.L.: Optimal brightness functions for optical flow estimation of deformable motion. IEEE Trans. Im. Proc. 3(2), 178–191 (1994)
Farid, H., Simoncelli, E.P.: Optimally rotation-equivariant directional derivative kernels. In: 7th Int’l Conf. Computer Analysis of Images and Patterns, Kiel (1997)
Farnebäck, G.: Fast and accurate motion est. using orient. tensors and param. motion models. In: ICPR, pp. 135–139 (2000)
Fleet, D.: Measurement of Image Velocity. Kluwer Academic Publishers, Dordrecht (1992)
Fleet, D.J., Langley, K.: Recursive filters for optical flow. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(1), 61–67 (1995)
Garbe, C.: Measuring Heat Exchange Processes at the Air-Water Interface from Thermographic Image Sequence Analysis. PhD thesis, Heidelberg University (2001)
Gupta, S., Prince, J.: On variable brightness optical flow for tagged mri. In: Information Processing in Medical Imaging, pp. 323–334 (1995)
Haerdle, W., Sperlich, S., Spokoiny, V.: Structural tests in additive regression. J. Amer. Stat. Acc. 96(456), 1333–1347 (2001)
Haußecker, H., Fleet, D.J.: Computing optical flow with physical models of brightness variation. PAMI 23(6), 661–673 (2001)
Haußecker, H., Spies, H.: Motion. In: Jähne, B., Haußecker, H., Geißler, P. (eds.) Handbook of Computer Vision and Applications, Academic Press, London (1999)
Haußecker, H., Spies, H., Jähne, B.: Tensor-based image sequence processing techniques for the study of dynamical processes. In: Proc. Int. Symp. On Real-Time Imaging and Dynamic Analysis, Japan 32(5), 704–711 (1998)
Horn, B.K., Schunk, B.G.: Determining optical flow. Art. Int. 17, 185–204 (1981)
Irani, M.: Multi-frame optical flow estimation using subspace constraints. In: IEEE International Conference on Computer Vision (ICCV), Corfu (1999)
Jähne, B.: Spatio-Temporal Image Processing. LNCS, vol. 751. Springer, Heidelberg (1993)
Jähne, B., Scharr, H., Körkel, S.: Principles of filter design. In: Handbook of Computer Vision and Applications, Academic Press, London (1999)
Koivunen, T., Nieminen, A.: Motion field restoration using vectormedian filtering on high definition television sequences. In: Proc. Vis. Comm. and Im. Proc.’90, vol. 1360, pp. 736–742 (1990)
Matthies, L.H., Szeliski, R., Kanade, T.: Kalman filter-based algorithms for estimating depth from image sequences. IJCV 3, 209–236 (1989)
Longuet-Higgins, H.C., Prazdny, K.: The interpretation of a moving retinal image. In: Proceedings of The Royal Society of London B, 208, pp. 385–397 (1980)
Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: DARPA Im. Underst. Workshop, pp. 121–130 (1981)
Nakamura, Y., Matsuura, T., Satoh, K., Ohta, Y.: Occlusion detectable stereo–occlusion patterns in camera matrix. In: CVPR, pp. 371–378 (1996)
Nestares, O., Fleet, D.J., Heeger, D.J.: Likelihood functions and confidence bounds for total-least-squares problems. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, Hilton Head, South Carolina, pp. 523–530. IEEE Computer Society Press, Los Alamitos (2000)
Scharr, H.: Optimal Operators in Digital Image Processing. PhD thesis, University of Heidelberg, Germany (2000)
Scharr, H., Küsters, R.: A linear model for simultaneous estimation of 3d motion and depth. In: IEEE Workshop on Motion and Video Computing, Orlando, Florida, USA, December 5-6 (2002)
Scharr, H., Küsters, R.: Simultaneous estimation of motion and disparity: Comparison of 2-, 3- and 5-camera setups. In: 2nd IASTED International Conference Visualization, Imaging and Image Processing (VIIP 2002), Malaga, Spain, September 9-12 (2002)
Schurr, U., Walter, A., Wilms, S., Spies, H., Kirchgessner, N., Scharr, H., Küsters, R.: Dynamics of leaf and root growth. 12th Int. Con. on Photosynthesis, PS 2001 (2001)
Spies, H., Jähne, B.: A general framework for image sequence processing. In: Fachtagung Informationstechnik, pp. 125–132. Universität Magdeburg (2001)
Spies, H., Kirchgeßner, N., Scharr, H., Jähne, B.: Dense structure estimation via regularised optical flow. In: VMV 2000, Saarbrücken, Germany, pp. 57–64 (2000)
Spies, H., Scharr, H.: Accurate optical flow in noisy image sequences. In: ICCV’01, Vancuver, Canada, pp. 587–592 (2001)
Szeliski, R.: A multi-view approach to motion and stereo. In: CVPR (1999)
Vedula, S., Baker, S., Rander, P., Collins, R., Kanade, T.: Threedimensional scene flow. In: ICCV 1999, pp. 722–729 (1999)
Vedula, S., Baker, S., Seitz, S., Collins, R., Kanade, T.: Shape and motion carving in 6d. In: CVPR 2000, pp. 592–598 (2000)
Weickert, J.: Applications of nonlinear diffusion in image processing and computer vision. Acta Math.Univ.Comenianae, Proc. of Algo. 2000 70(1), 33–50 (2001)
Weickert, J., Schnörr, C.: Variational optic flow computation with a spatio-temporal smoothness constraint. Technical Report 15/2000, Comp. Vis., Graphics, and Patt. Recogn. Group, Dept. of Math. and Comp. Sci., Univ. Mannheim, Germany, July (2000)
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Scharr, H. (2007). Towards a Multi-camera Generalization of Brightness Constancy. In: Jähne, B., Mester, R., Barth, E., Scharr, H. (eds) Complex Motion. IWCM 2004. Lecture Notes in Computer Science, vol 3417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69866-1_7
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DOI: https://doi.org/10.1007/978-3-540-69866-1_7
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