Abstract
Current approaches to cell motion analysis rely on cell tracking. In certain cases, the trajectories of each cell is not as informative as a representation of the overall motion in the scene. In this paper, we extend a cell motion descriptor and provide methods for the intuitive visualization and querying of cell motion. Our approach allows for searches of scale- and rotation-invariant motion signatures, and we develop a desktop application that researchers can use to query biomedical video quickly and efficiently. We demonstrate this application on synthetic video sets and in vivo microscopy video of cells in a mouse liver.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yilmaz, A., Javed, O., Shah, M.: Object tracking: A survey. ACM Comput. Surv. 38(4), 13 (2006)
Mukherjee, D., Ray, N., Acton, S.: Level set analysis for leukocyte detection and tracking. IEEE Trans. on Image Processing 13(4), 562–572 (2004)
Debeir, O., Van Ham, P., Kiss, R., Decaestecker, C.: Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes. IEEE Trans. on Medical Imaging 24(6), 697–711 (2005)
Li, K., Chen, M., Kanade, T.: Cell population tracking and lineage construction with spatiotemporal context. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 295–302. Springer, Heidelberg (2007)
Souvenir, R., Kraftchick, J., Lee, S., Clemens, M., Shin, M.: Cell motion analysis without explicit tracking. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–7 (June 2008)
Sbalzarini, I.F., Koumoutsakos, P.: Feature point tracking and trajectory analysis for video imaging in cell biology. Journal of Structural Biology 151(2), 182–195 (2005)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of the 7th International Joint Conference on Artificial Intelligence (IJCAI 1981), pp. 674–679 (1981)
Hinz, S., Baumgartner, A.: Road Extraction in Urban Areas Supported by Context Objects. In: Int’l Archives of Photogrammetry and Remote Sensing, vol. 33, pp. 405–412 (2000)
Pless, R., Jurgens, D.: Road extraction from motion cues in aerial video. In: Proc. of the ACM Conf. on Geographic Information Systems, pp. 31–38 (2004)
Roth, M., Freeman, W.T.: Orientation histograms for hand gesture recognition. In: Intl. Workshop on Automatic Face and Gesture Recognition (1995)
Ballard, D.H.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13(2), 111–122 (1981)
Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. In: Vitányi, P.M.B. (ed.) EuroCOLT 1995. LNCS, vol. 904, pp. 23–37. Springer, Heidelberg (1995)
Mallick, S., Zhu, Y., Kriegman, D.: Detecting particles in cryo-EM micrographs using learned features. Journal of Structural Biology 145(1-2), 52–62 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Souvenir, R., Kraftchick, J.P., Shin, M.C. (2008). Intuitive Visualization and Querying of Cell Motion. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_101
Download citation
DOI: https://doi.org/10.1007/978-3-540-89639-5_101
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89638-8
Online ISBN: 978-3-540-89639-5
eBook Packages: Computer ScienceComputer Science (R0)