More specific information is included in each subfield.
Subfields and Concepts
See Category:Computer Vision for some of its subfields.
- Image Preprocessing
- Image Augmentation
- Low-level Vision
- Digital Image Processing
- Feature extraction
- Hough Transform
- Feature detection
- Edge detection
- Corner detection
- Optical flow
- Intermediate-level Vision
- Recognition tasks
- Face recognition
- Object detection
- Face detection
- Pedestrian detection
- Image segmentation
- 3D reconstruction
- Motion analysis
- Recognition tasks
- High-level Vision / Image Understanding
- Structure from Motion
- Simultaneous Localization and Mapping (SLAM)
- Optical Character Recognition (OCR)
- Place and Object recognition
- Object detection
- Object localization
- Object classification
- Scene classification
- Scene recognition
- Semantic Scene Understanding
- Feature descriptors
- Scale-invariant feature transform (SIFT)
- Speeded up robust features (SURF)
- Histogram of oriented gradients (HOG)
- Medical Image Computing / Medical Image Analysis
- Computer Graphics
- Inverse Graphics
- UCF Computer Vision by Mubarak Shah
- Image and video processing by Guillermo Sapiro (Youtube )
- Advanced Vision by Bob Fisher
- Deep Learning in Computer Vision - Coursera
- CS 143: Introduction to Computer Vision by James Hays
- CS 223B: Introduction to Computer Vision by Fei-Fei Li
- CSE576: Computer Vision by Linda Shapiro
- Introduction to Computer Vision by Robert Collins
- Computer Vision by John Daugman
- Computer Vision by Lin Zhang
- Advances in Computer Vision by MIT
- 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.
- 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.
- Jahne, B., Geissler, P., & Haussecker, H. (1999). Handbook of Computer Vision and Applications with CD-ROM. Morgan Kaufmann Publishers Inc.
- 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.
- Hyvarinen, 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. Springer.
- OpenCV - C++, C, Python and Java interfaces that support Windows, Linux, Mac OS, iOS and Android
- SimpleCV - Framework using Python
- OpenNI - Official website was shut down by Apple Inc.
- OpenBR - Open Source Biometric Recognition
- PCL - Point Cloud Library
- ICL - Image Component Library
- Image Processing Toolbox - MATLAB
- Computer Vision System Toolbox- MATLAB
- VXL - C++
- Processing - IDE for Computational Artitsts promoting software literacy within the visual arts
- Computer Vision and Pattern Recognition - Google Scholar Metrics (Top Publications)
- ComputerVision wikia - Portal on all aspects of Vision and Image Processing
- Awesome-Computer-Vision (Github) - A curated list of resources
- Collection of Computer Vision notes - York University
- Computer Vision on Google+ - online community
- CVonline - The evolving, distributed, non-proprietary, on-line compendium of Computer Vision
- Computer VIsion systems in a nutshell
- Have We Forgotten about Geometry in Computer Vision?