Dense Correspondence and Optical Flow Estimation Using Gabor, Schmid and Steerable Descriptors

详细信息    查看全文

• 关键词：Dense correspondence ; Optical flow ; SIFT ; Schmid filters ; Gabor filters ; Steerable filters
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9474
• 期：1
• 页码：406-415
• 全文大小：2,369 KB
• 参考文献：1. Baghaie, A., Yu, Z.: Curvature-based registration for slice interpolation of medical images. In: Zhang, Y.J., Tavares, J.M.R.S. (eds.) CompIMAGE 2014. LNCS, vol. 8641, pp. 69–80. Springer, Heidelberg (2014)
  2.Baghaie, A., D’souza, R.M., Yu, Z.: Sparse And Low Rank Decomposition Based Batch Image Alignment for Speckle Reduction of retinal OCT Images (2014). arXiv preprint arXiv:​1411.​4033
  3.Baghaie, A., Yu, Z., D’souza, R.M.: State-of-the-art in retinal optical coherence tomography image analysis. Quant. Imaging Med. Surg. 5(4), 603–617 (2015). doi:10.​3978/​j.​issn.​2223-4292.​2015.​04.​08
  4.Baghaie, A., D’souza, R.M., Yu, Z.: Application of Independent Component Analysis Techniques in Speckle Noise Reduction of Single-Shot Retinal OCT Images (2015). arXiv preprint arXiv:​1502.​05742
  5. Lillesand, T., Kiefer, R.W.: Remote Sensing and Image Interpretation. Wiley, New York (2014)
  6.Li, Q., Wang, G., Liu, J., Chen, S.: Robust scale-invariant feature matching for remote sensing image registration. IEEE Geosci. Remote Sens. Lett. 6(2), 287–291 (2009)CrossRef
  7.Zitova, B., Flusser, J.: Image registration methods: a survey. Image Vis. Comput. 21(11), 977–1000 (2003)CrossRef
  8. Baghaie, A., Yu, Z., D’souza, R.M.: Fast mesh-based medical image registration. In: Bebis, G., et al. (eds.) ISVC 2014, Part II. LNCS, vol. 8888, pp. 1–10. Springer, Heidelberg (2014)
  9.Tafti, A.P., Hassannia, H., Yu, Z.: siftservice.com-Turning a Computer Vision algorithm into a World Wide Web Service (2015). arXiv preprint arXiv:​1504.​02840
  10.Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)CrossRef
  11.Tafti, A.P., Kirkpatrick, A.B., Alavi, Z., Owen, H.A., Zeyun, Y.: Recent advances in 3D SEM surface reconstruction. Micron 78, 54–66 (2015)CrossRef
  12. Tafti, A.P., Kirkpatrick, A.B., Owen, H.A., Yu, Z.: 3D microscopy vision using multiple view geometry and differential evolutionary approaches. In: Bebis, G., et al. (eds.) ISVC 2014, Part II. LNCS, vol. 8888, pp. 141–152. Springer, Heidelberg (2014)
  13.Tafti, A.P., Baghaie, A., Kirkpatrick, A.B., Owen, H.A., D’Souza, R.M., Yu, Z.: A Comparative study on the application of SIFT, SURF, BRIEF and ORB for 3D surface reconstruction of electron microscopy images. In: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization (2016)
  14.Johnson, A.E., Hebert, M.: Recognizing objects by matching oriented points. In: 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Proceedings. IEEE (1997)
  15. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006) CrossRef
  16.Wang, H., Klser, A., Schmid, C., Liu, C.-L.: Action recognition by dense trajectories. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (2011)
  17.Tola, E., Lepetit, V., Fua, P.: Daisy: an efficient dense descriptor applied to wide-baseline stereo. IEEE Trans. Pattern Anal. Mach. Intell. 32(5), 815–830 (2010)CrossRef
  18.Sangineto, E.: Pose and expression independent facial landmark localization using dense-SURF and the Hausdorff distance. IEEE Trans. Pattern Anal. Mach. Intell. 35(3), 624–638 (2013)CrossRef
  19.Dalal, N.,Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1. IEEE (2005)
  20.Gabor, D.: Theory of communication. part 1: the analysis of information. J. Inst. Electr. Eng. III. Radio Commun. Eng. 93(26), 429–441 (1946)
  21.Movellan, J.R.: Tutorial on Gabor filters. Open Source Document (2002)
  22. Ilonen, J., Kmrinen, J.-K., Kllvinen, H.: Efficient computation of Gabor features. Lappeenranta University of Technology, Lappeenranta (2005)
  23.Schmid, C.: Constructing models for content-based image retrieval. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 2. IEEE (2001)
  24.Freeman, W.T., Adelson, E.H.: The design and use of steerable filters. IEEE Trans. Pattern Anal. Mach. Intell. 9, 891–906 (1991)CrossRef
  25.Jacob, M., Unser, M.: Design of steerable filters for feature detection using canny-like criteria. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1007–1019 (2004)CrossRef
  26.Aguet, F., Jacob, M., Unser, M.: Three-dimensional feature detection using optimal steerable filters. In: IEEE International Conference on Image Processing, ICIP 2005, vol. 2. IEEE (2005)
  27.Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Intern. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef
  28. Mikolajczyk, K., Schmid, C.: An affine invariant interest point detector. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part I. LNCS, vol. 2350, pp. 128–142. Springer, Heidelberg (2002) CrossRef
  29.Liu, C., Yuen, J., Torralba, A.: Sift flow: dense correspondence across scenes and its applications. IEEE Trans. Pattern Anal. Mach. Intell. 33(5), 978–994 (2011)CrossRef
  30.Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo (2014)
  31.Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.: A database and evaluation methodology for optical flow. Intern. J. Comput. Vis. 92(1), 1–31 (2011)CrossRef
  32.Malin, M.C., Edgett, K.S., Carr, M.H., Danielson, G.E., Davies, M.E., Hartmann, W.K., Ingersoll, A.P., James, P.B., Masursky, H., McEwen, A.S., Soderblom, L.A., Thomas, P., Veverka, J., Caplinger, M.A., Ravine, M.A., Soulanille, T.A., Warren, J.L.: New Gully Deposit in a Crater in Terra Sirenum: Evidence That Water Flowed on Mars in This Decade? In: NASA’s Planetary Photojournal, MOC2-1618, 6 December 2006. http://​photojournal.​jpl.​nasa.​gov/​
  33.Yang, G., Stewart, C.V., Sofka, M., Tsai, C.-L.: Registration of challenging image pairs: initialization, estimation, and decision. IEEE Trans. Pattern Anal. Mach. Intell. 29(11), 1973–1989 (2007)CrossRef
  
• 作者单位：Ahmadreza Baghaie (25)
  Roshan M. D’Souza (25)
  Zeyun Yu (25)
  
  25. College of Engineering and Applied Science, UW-Milwaukee, Milwaukee, WI, USA
  
• 丛书名：Advances in Visual Computing
• ISBN：978-3-319-27857-5
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In this paper, the use of three dense descriptors, namely Schmid, Gabor and steerable descriptors, is introduced and investigated for optical flow estimation and dense correspondence of different scenes and compared with the well-known dense SIFT/SIFTFlow. Several examples of optical flow estimation and dense correspondence across scenes with high variations in the intensity levels, difference in the presence of features and different misalignment models (rigid, deformable, homography etc.) are studied and the results are quantitatively/qualitatively compared with dense SIFT/SIFTFlow. The proposed dense descriptors provide comparable or better results than dense SIFT/SIFTFlow which shows the high potential in this area for more thorough investigations.