This page gives a brief overview of our research on multiple motions.
The motion patterns that occur in natural scenes are more complex than
the state-of-the art motion models. A particular case of more complex
motion patterns are multiple overlaid motions that occur in natural
environments due to transparencies, reflections, and occlusions.
We first studied multiple overlaid motions in the context of vision science as an extension of research on intrinsic dimension (Zetzsche & Barth, 1990) and visual motion selectivity (Barth & Watson, 2000). Initially, the research on multiple motions was supported by the DAAD
grant A/99/22641 to Cicero Mota, who came to visit us from the
University of Amazonas in Brazil. We worked out an analytical solution
for the problem of estimating transparent motion layers (Mota et al.,
2001). The solution is based on a nontrivial linearization of the
nonlinear problem. We also performed experiments related to the
perception of multiple motion layers (Barth et al., 2001; Mota et al., 2004)
and we could predict the ability of human observers to detect the
number of motion layers. We argued that detection is limited by the
angular separation of the velocities of the layers.
Subsequent research was supported by the DFG - see LOCOMOTOR
page - and focused on the mathematical and technical aspects of the
problem. We first generalized our approach to include more robust
regularization (Stuke et al., 2003) and block-matching (Stuke et al., 2003) techniques. We then extended our analysis to the case of occluded motions (Barth et al., 2003; Mota et al., 2005) and more complex patterns (Scharr et al., 2005). Then we went back to the more basic issue of estimating multiple orientations (Mota et al., 2004; Aach et al., 2006).
We then succeeded in solving the more general problem of how to
simulteanusly detect and estimate N subspaces (in images this would be
orientations and in movies motions) for signals of any dimension (Stuke et al., 2006).
This allows us, for example, to estimate an arbitrary number of
overlaid orientations in any dimension. Finally, we have shown how to
extent the approach to multispectral images (Mota et al., 2006).
Here we list the publications referenced above. A more comprehensive list of publications can be found on the LOCOMOTOR page and on the more frequently updated INB publications page.
- Zetzsche, C. & Barth, E. (1990).
Fundamental limits of linear filters in the visual processing of
two-dimensional signals. Vision Research, Vol. 30, 1111-1117.
- Barth, E. & Watson, A. B. (2000) A geometric framework for
nonlinear visual coding. Optics Express Vol. 7. No. 4, 155-165.
- Barth, E., Dorr, M., Stuke, I., & Mota C. (2001). Theory and
some data for up to four transparent motions. Perception, 30
- Mota, C., Dorr, M., Stuke, I., & Barth, E. (2004).
Categorization of Transparent-Motion Patterns Using the Projective
Plane. International Journal of Computer & Information Science,
Vol. 5, No. 2: 129-140.
- Mota, C., Stuke, I, & Barth, E. (2001). Analytic solutions for
multiple motions. IEEE International Conference on Image Processing,
Vol. II, 917-920.
- I. Stuke, T. Aach, C. Mota, and E. Barth (2003). Estimation of
multiple motions: regularization and performance evaluation. In B.
Vasudev, T. R. Hsing, A. G. Tescher, and T. Ebrahimi, editors, Image
and Video Communications and Processing 2003, Proceedings of SPIE,
volume 5022, pages 75-86.
- Ingo Stuke, Til Aach, Erhardt Barth, and Cicero Mota (2003).
Estimation of Multiple Motions by Block Matching. In W. Dosch and R. Y.
Lee, editors, Proceedings of the ACIS 4th International Conference on
Software Engineering, Artificial Intelligence, Networking and
Parallel/Distributed Computing (SNPD'03), Lübeck, Germany, October
16-18, 2003, pages 358-62.
- Barth, E., Stuke, I., Aach, T., & Mota, C. (2003).
Spatio-Temporal Motion Estimation for Transparency and Occlusions.
Proceedings of IEEE International Conference on Image Processing, Vol.
- C. Mota, I. Stuke, T. Aach, and E. Barth (2005). Spatial and
spectral analysis of occluded motions. Signal Processing: Image
Communication. Elsevier Science, 20-6:529-536.
- H. Scharr, I. Stuke, C. Mota, and E. Barth (2005). Estimation of
Transparent Motions with Physical Models for Additional Brightness
Variation. In European Signal Pocessing Conference.
- C. Mota, T. Aach, I. Stuke, and E. Barth (2004). Estimation of
multiple orientations in multi-dimensional signals. In IEEE
International Conference on Image Processing, 2665-2668.
- Aach T., Mota C., Stuke I., Mühlich M., & Barth E. (2006)
Analysis of Superimposed Oriented Patterns, IEEE Transactions on Image
Processing, Vol. 15, No. 12, 3690-3700.
- Stuke, I., Barth, E. & Mota, C., (2006) Estimation of Multiple
Orientations and Multiple Motions in Multi-Dimensional Signals. IEEE
XIX Brazilian Symposium on Computer Graphics and Image Processing
- Mota, C., Stuke, I., & Barth, E. (2006). The Intrinsic
Dimension of Multispectral Images. MICCAI Workshop on Biophotonics
Imaging for Diagnostics and Treatment, Copenhagen.