Applications of Computer Vision in Micro/Nano Observation

Nowadays, micro/nano science and technology has been one of the most attractive research fields. However, real time and accurate observation in micro/nano manipulation is a top important enabling technique. Most recently, with the great development of microscopes and computer vision techniques, real time visualization, including 2D motion measurement and 3D reconstruction, on micro/nano scale is becoming possible.

[1]  H.N. Nair,et al.  Robust focus ranging , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  Peter Lawrence,et al.  An Investigation of Methods for Determining Depth from Focus , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Shree K. Nayar,et al.  Shape from focus system , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Stefano Soatto,et al.  Learning Shape from Defocus , 2002, ECCV.

[5]  Stefano Soatto,et al.  Observing Shape from Defocused Images , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[6]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[7]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[8]  Alex Pentland,et al.  A New Sense for Depth of Field , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Andrea Giachetti,et al.  Refinement of Optical Flow Estimation and Detection of Motion Edges , 1996, ECCV.

[10]  Murali Subbarao,et al.  Depth from defocus: A spatial domain approach , 1994, International Journal of Computer Vision.

[11]  Teresa C. S. Azevedo,et al.  3D Object Reconstruction from Uncalibrated Images using an Off-the-Shelf Camera , 2009 .

[12]  Ajit Singh,et al.  An estimation-theoretic framework for image-flow computation , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[13]  Stefano Soatto,et al.  Observing Shape from Defocused Images , 2004, International Journal of Computer Vision.

[14]  Shree K. Nayar,et al.  Real-Time Focus Range Sensor , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Alex Pentland,et al.  Simple range cameras based on focal error , 1994 .

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

[17]  Stanley Osher,et al.  A technique for calibrating derivative security pricing models: numerical solution of an inverse problem , 1997 .

[18]  Peyman Milanfar,et al.  Fundamental performance limits in image registration , 2004, IEEE Trans. Image Process..

[19]  Bernd Girod,et al.  Depth from Defocus of Structured Light , 1990, Other Conferences.

[20]  Mats Gökstorp,et al.  Computing depth from out-of-focus blur using a local frequency representation , 1994, International Conference on Pattern Recognition.

[21]  V. Bove Entropy-based depth from focus , 1993 .

[22]  C. Menq,et al.  Visually Servoed 3-D Alignment of Multiple Objects with Subnanometer Precision , 2008, IEEE Transactions on Nanotechnology.

[23]  Subhasis Chaudhuri,et al.  On defocus, diffusion and depth estimation , 2007, Pattern Recognit. Lett..

[24]  João Manuel R. S. Tavares,et al.  Three-dimensional reconstruction and characterization of human external shapes from two-dimensional images using volumetric methods , 2010, Computer methods in biomechanics and biomedical engineering.

[25]  Mats Gokstorp Computing depth from out-of-focus blur using a local frequency representation , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[26]  Gaoliang Dai,et al.  Determining the residual nonlinearity of a high-precision heterodyne interferometer , 1999 .

[27]  Stefano Soatto,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE IEEE TRANSACTION OF PATTERN RECO , 2022 .

[28]  Naoki Asada,et al.  Edge and Depth from Focus , 2004, International Journal of Computer Vision.

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