What are major algorithms for computer vision?
SIFT and SURF for feature-point extraction. Used for object recognition, Image registration.
Viola-Jones algorithm, for object (especially face) detection in real time. One of the most elegant algorithms, one of my favorites.
'Eigenfaces' approach, using PCA for dimension reduction. Used in face recognition. Has a very intuitive approach and yet it is mathematically strong.
Lucas-Kanade algorithm for optical flow calculation. Used for tracking, stereo registration. Also the Horn-Schunk algorithm.
Mean-shift algorithm for fast tracking of object. Not very robust, but easy to use, and very useful in specific applications.
Kalman filter, again for object tracking, using point features for tracking. Great use in many fields like computer vision, control systems, etc.
Adaptive thresholding (and other thresholding techniques), because thresholding is much more important than thought.
Machine learning algorithms like SVM's, KNN, Naive Bayes, etc. are also very important in the field of computer vision.
Iterative Closest Point (ICP) to co-register two or more 3D pointclouds together
Semi Global Matching (SGM) and Semi Global Block Matching (SGBM) algorithms which generate a depth image from stereo images
Feature Point Histograms for detecting features in 3D space