The following outline is provided as an overview of and topical guide to computer vision: Computer vision – interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring digital images (through image sensors), image processing, and image analysis, to reach an understanding of digital images. In general, it deals with the extraction of high-dimensional data from the real world in order to produce numerical or symbolic information that the computer can interpret. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply its theories and models for the construction of computer vision systems. As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. Branches of computer vision Computer stereo vision Underwater computer vision History of computer vision History of computer vision Computer vision subsystems Image enhancement Image denoising Image histogram Inpainting Histogram equalization Tone mapping Retinex Gamma correction Anisotropic diffusion (Perona–Malik equation) Transformations Affine transform Homography (computer vision) Hough transform Radon transform Walsh–Hadamard transform Filtering, Fourier and wavelet transforms and image compression Image compression Filter bank Gabor filter JPEG 2000 Adaptive filtering Color vision Visual perception Human visual system model Color matching function Color space Color appearance model Color management system Color mapping Color model Color profile Feature extraction Active contour Blob detection Canny edge detector Contour detection Edge detection Edge linking Harris Corner Detector Histogram of oriented gradients (HOG) Random sample consensus (RANSAC) Scale-invariant feature transform (SIFT) Pose estimation Bundle adjustment Articulated body pose estimation (BoPoE) Direct linear transformation (DLT) Epipolar geometry Fundamental matrix Pinhole camera model Projective geometry Trifocal tensor Registration Active appearance model (AAM) Cross-correlation Geometric hashing Graph cut segmentation Least squares estimation Image pyramid Image segmentation Level-set method Markov random fields Medial axis Motion field Motion vector Multispectral imaging Normalized cut segmentation Optical flow Particle filtering Scale space Visual recognition Object recognition Scale-invariant feature transform (SIFT) Gesture recognition Bag-of-words model in computer vision Kadir–Brady saliency detector Eigenface Commercial computer vision systems 5DX Aphelion (software) Microsoft PixelSense Poseidon drowning detection system Visage SDK Applications 3D reconstruction from multiple images Audio-visual speech recognition Augmented reality