Motion microscopy for visualizing and quantifying small motions

Significance Humans have difficulty seeing small motions with amplitudes below a threshold. Although there are optical techniques to visualize small static physical features (e.g., microscopes), visualization of small dynamic motions is extremely difficult. Here, we introduce a visualization tool, the motion microscope, that makes it possible to see and understand important biological and physical modes of motion. The motion microscope amplifies motions in a captured video sequence by rerendering small motions to make them large enough to see and quantifies those motions for analysis. Amplification of these tiny motions involves careful noise analysis to avoid the amplification of spurious signals. In the representative examples presented in this study, the visualizations reveal important motions that are invisible to the naked eye. Although the human visual system is remarkable at perceiving and interpreting motions, it has limited sensitivity, and we cannot see motions that are smaller than some threshold. Although difficult to visualize, tiny motions below this threshold are important and can reveal physical mechanisms, or be precursors to large motions in the case of mechanical failure. Here, we present a “motion microscope,” a computational tool that quantifies tiny motions in videos and then visualizes them by producing a new video in which the motions are made large enough to see. Three scientific visualizations are shown, spanning macroscopic to nanoscopic length scales. They are the resonant vibrations of a bridge demonstrating simultaneous spatial and temporal modal analysis, micrometer vibrations of a metamaterial demonstrating wave propagation through an elastic matrix with embedded resonating units, and nanometer motions of an extracellular tissue found in the inner ear demonstrating a mechanism of frequency separation in hearing. In these instances, the motion microscope uncovers hidden dynamics over a variety of length scales, leading to the discovery of previously unknown phenomena.

[1]  Vincent Laude,et al.  Guiding and bending of acoustic waves in highly confined phononic crystal waveguides , 2004 .

[2]  Massimo Ruzzene,et al.  Experimental analysis of wave propagation in periodic grid-like structures , 2005, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[3]  David J. Fleet,et al.  Computation of component image velocity from local phase information , 1990, International Journal of Computer Vision.

[4]  Gilles Lubineau,et al.  Using Image Gradients to Improve Robustness of Digital Image Correlation to Non-uniform Illumination: Effects of Weighting and Normalization Choices , 2015 .

[5]  Frédo Durand,et al.  Eulerian video magnification and analysis , 2016, Commun. ACM.

[6]  Michael Unser,et al.  Splines: a perfect fit for signal and image processing , 1999, IEEE Signal Process. Mag..

[7]  Roozbeh Ghaffari,et al.  Tectorial membrane material properties in Tecta(Y)(1870C/+) heterozygous mice. , 2010, Biophysical journal.

[8]  Frédo Durand,et al.  Eulerian video magnification for revealing subtle changes in the world , 2012, ACM Trans. Graph..

[9]  O. S. Salawu Detection of structural damage through changes in frequency: a review , 1997 .

[10]  D. M. Freeman,et al.  Longitudinally propagating traveling waves of the mammalian tectorial membrane , 2007, Proceedings of the National Academy of Sciences.

[11]  Alessandro Spadoni,et al.  Generation and control of sound bullets with a nonlinear acoustic lens , 2009, Proceedings of the National Academy of Sciences.

[12]  O. Glockl,et al.  Reduction of Guided Acoustic Wave Brillouin Scattering in Photonic Crystal Fibers , 2007, 2007 European Conference on Lasers and Electro-Optics and the International Quantum Electronics Conference.

[13]  William T. Freeman,et al.  Presented at: 2nd Annual IEEE International Conference on Image , 1995 .

[14]  K. Bertoldi,et al.  Harnessing buckling to design tunable locally resonant acoustic metamaterials. , 2014, Physical review letters.

[15]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[16]  Eero P. Simoncelli,et al.  A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients , 2000, International Journal of Computer Vision.

[17]  M. Ruzzene,et al.  Dynamics of Phononic Materials and Structures: Historical Origins, Recent Progress, and Future Outlook , 2014 .

[18]  Frédo Durand,et al.  Noise-optimal capture for high dynamic range photography , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Roozbeh Ghaffari,et al.  Porosity controls spread of excitation in tectorial membrane traveling waves. , 2014, Biophysical journal.

[20]  J. C. Wachel,et al.  Piping Vibration Analysis. , 1990 .

[21]  Roozbeh Ghaffari,et al.  Longitudinal spread of mechanical excitation through tectorial membrane traveling waves , 2015, Proceedings of the National Academy of Sciences.

[22]  S. Cummer,et al.  One path to acoustic cloaking , 2007 .

[23]  A. Melling,et al.  Principles and practice of laser-Doppler anemometry , 1976 .

[24]  Derek Nowrouzezahrai,et al.  Learning hatching for pen-and-ink illustration of surfaces , 2012, TOGS.

[25]  Jonathan Ashmore,et al.  The cochlea , 2000, Current Biology.

[26]  Richard Szeliski,et al.  Noise Estimation from a Single Image , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[27]  J. J. Zwislocki Symposium on cochlear mechanics: Where do we stand after 50 years of research? , 1980, The Journal of the Acoustical Society of America.

[28]  D. J. Ewins,et al.  Modal Testing: Theory and Practice , 1984 .

[29]  P. Dallos,et al.  The Cochlea: Springer Handbook of Auditory Research , 1996 .

[30]  J J Zwislocki,et al.  Five decades of research on cochlear mechanics. , 1980, The Journal of the Acoustical Society of America.

[31]  David J. Fleet Measurement of image velocity , 1992 .

[32]  Frédo Durand,et al.  Phase-based video motion processing , 2013, ACM Trans. Graph..

[33]  Frédo Durand,et al.  Motion magnification , 2005, ACM Trans. Graph..

[34]  L. Hermans,et al.  MODAL TESTING AND ANALYSIS OF STRUCTURES UNDER OPERATIONAL CONDITIONS: INDUSTRIAL APPLICATIONS , 1999 .

[35]  Frédo Durand,et al.  Riesz pyramids for fast phase-based video magnification , 2014, 2014 IEEE International Conference on Computational Photography (ICCP).

[36]  Junichi Nakamura,et al.  Image Sensors and Signal Processing for Digital Still Cameras , 2005 .

[37]  Alan V. Oppenheim,et al.  Discrete-Time Signal Pro-cessing , 1989 .

[38]  I. Thalmann,et al.  Collagen of accessory structures of organ of Corti. , 1993, Connective tissue research.

[39]  Justin A. Blaber,et al.  Ncorr: Open-Source 2D Digital Image Correlation Matlab Software , 2015, Experimental Mechanics.

[40]  Roozbeh Ghaffari,et al.  Tectorial membrane travelling waves underlie abnormal hearing in Tectb mutant mice , 2010, Nature communications.

[41]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.