Keywords
dynamical image
live cell
cytology
optical flow
How to Cite
Abstract
The algorithm for the determination of 3D-characteristics of a dynamic biological object based on the recovery of a stereo pair was proposed. Images for stereo pair construction were obtained via a single camera before and after the displacement of the object. The algorithm is based on the example of living one-celled organisms.
References
Aggarwal, J. and Ryoo, M., Human Activity Analysis: A Review, ACM Comput. Surv., Vol. 43, No. 3, April 2011, pp. 16:1–16:43.
Liao, W., Aggarwal, S., and Aggarwal, J., The Reconstruction of Dynamic 3D Structure of Biological Objects Using Stereo Microscope Images, Vol. 9, No. 4, 1997, pp. 166–178.
Stockman, G. and Shapiro, L. G., Computer Vision, Prentice Hall PTR, Upper Saddle River, NJ, USA, 1st ed., 2001. O. Nedzved, S. Ablameyko 75 Figure 17. 3D cell reconstruction 76 Determination of Volume Characteristics of Cells 2010, pp. 282–285.
Yu, C., Dian-ren, C., Yang, L., and Lei, C., Otsu’s Thresholding Method Based on Gray Level-gradient Two-dimensional Histogram, In: Proceedings of the 2Nd International Asia Conference on Informatics in Control, Automation and Robotics - Volume 3, CAR’10, IEEE Press, Piscataway, NJ, USA,
Sabater, N., Blanchet, G., Moisan, L., Almansa, A., and Morel, J.-M., Review of low-baseline stereo algorithms and benchmarks, In: Image Signal Process. Remote Sens. XVI, edited by L. Bruzzone, Vol. 7830, Oct. 2010, pp. 783005–783005–12.
Sabater, N., Almansa, A., and Morel, J.-M., Meaningful matches in stereovision. IEEE Trans. Pattern Anal. Mach. Intell., Vol. 34, No. 5, May 2012, pp. 930–42.
Bhalerao, R. H., Gedam, S. S., and Almansa, A. A., Fast epipolar resampling of trinocular linear scanners images using Chandrayaan-1 TMC dataset, In: 2013 IEEE Second Int. Conf. Image Inf. Process., IEEE, Dec. 2013, pp. 12–16.
Slabaugh, G. G., Culbertson, W. B., Malzbender, T., Stevens, M. R., and Schafer, R. W., Methods for Volumetric Reconstruction of Visual Scenes. International Journal of Computer Vision, Vol. 57, No. 3, 2004, pp. 179–199.
Furukawa, Y. and Ponce, J., Accurate, dense, and robust multiview stereopsis, Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 32, No. 8, 2010, pp. 1362–1376.
Hartley, R. I. and Zisserman, A., Multiple View Geometry in Computer Vision, Cambridge University Press, ISBN: 0521540518, 2nd ed., 2004.