Ioannis Kourouklides
Tags: Visual edit apiedit
Tags: Visual edit apiedit
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''See [http://kourouklides.wikia.com/wiki/Category:Computer_Vision Category:Computer Vision] for some of its subfields.''
 
''See [http://kourouklides.wikia.com/wiki/Category:Computer_Vision Category:Computer Vision] for some of its subfields.''
 
* [[Digital Image Processing|Low-level Vision / Digital Image Processing]]
 
* [[Digital Image Processing|Low-level Vision / Digital Image Processing]]
  +
** Feature extraction
* Medium-level Vision
 
  +
** Edge detection
* High-level Vision
 
  +
** Optical flow
 
* Intermediate-level Vision
  +
** Object recognition
  +
** 3D reconstruction
  +
** Motion analysis
 
* High-level Vision / Image Understanding
  +
** [[Machine Learning]]
 
* Structure from Motion
 
* Structure from Motion
* [[Medical Imaging]]
+
* [[Medical Imaging|Medical Image Computing / Medical Image Analysis]]
 
* [[Computer Graphics]]
 
* [[Computer Graphics]]
   

Revision as of 06:41, 18 December 2016

Reconstruct-3D

This page contains resources about Computer Vision and Image Processing in general.

More specific information is included in each subfield.

Subfields

See Category:Computer Vision for some of its subfields.

Online Courses

Video Lectures


Lecture Notes

Books

Practical

  • Howse, J. (2013). OpenCV Computer Vision with Python. Packt Publishing Ltd.
  • Demaagd, K., Oliver, A., Oostendorp, N., & Scott, K. (2012). Practical Computer Vision with SimpleCV: The Simple Way to Make Technology See. O'Reilly Media, Inc.
  • Solem, J. E. (2012). Programming Computer Vision with Python: Tools and algorithms for analyzing images. O'Reilly Media, Inc.
  • Bradski, G., & Kaehler, A. (2008). Learning OpenCV: Computer Vision with the OpenCV Library. O'Reilly Media, Inc.

Introductory

  • Szeliski, R. (2010). Computer Vision: Algorithms and Applications. Springer.
  • Zisserman, A., & Hartley, R. (2004). Multiple View Geometry in Computer Vision. Cambridge University Press.
  • Forsyth, D. A., & Ponce, J. (2002). Computer Vision: A Modern Approach. Prentice Hall.

Advanced

  • Jahne, B., Geissler, P., & Haussecker, H. (1999). Handbook of Computer Vision and Applications with CD-ROM. Morgan Kaufmann Publishers Inc.

Specialized

  • Prince, S. J. D. (2012). Computer Vision: Models, Learning, and Inference. Cambridge University Press.
  • Nowozin, S., & Lampert, C. H. (2011). Structured Prediction and Learning in Computer Vision. Foundations and Trends in Computer Graphics and Vision, 6(3-4), 3-4.
  • Hyvärinen, A., Hurri, J. & Hoyer, P. O. (2009). Natural Image Statistics: A Probabilistic Approach to Early Computational Vision. Springer.
  • Ma, Y. (Ed.). (2004). An Invitation to 3D Vision: From Images to Geometric Models (Vol. 26). Springer.

Software

Other Resources