Table of Contents
28 relations: Advanced Video Coding, Block-matching algorithm, Computer vision, Corner detection, Correspondence problem, Daniel Cremers, Data compression, Digital image processing, Discrete cosine transform, Film frame, Graphics processing unit, High Efficiency Video Coding, Image registration, Macroblock, Motion, Motion compensation, Moving object detection, Moving Picture Experts Group, Optical flow, Phase correlation, Pixel, Random sample consensus, Scale-invariant feature transform, Simultaneous localization and mapping, Taylor & Francis, Video coding format, Vision processing unit, Well-posed problem.
- Motion (physics)
- Motion in computer vision
- Video processing
Advanced Video Coding
Advanced Video Coding (AVC), also referred to as H.264 or MPEG-4 Part 10, is a video compression standard based on block-oriented, motion-compensated coding.
See Motion estimation and Advanced Video Coding
Block-matching algorithm
A Block Matching Algorithm is a way of locating matching macroblocks in a sequence of digital video frames for the purposes of motion estimation.
See Motion estimation and Block-matching algorithm
Computer vision
Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions.
See Motion estimation and Computer vision
Corner detection
Corner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image.
See Motion estimation and Corner detection
Correspondence problem
The correspondence problem refers to the problem of ascertaining which parts of one image correspond to which parts of another image, where differences are due to movement of the camera, the elapse of time, and/or movement of objects in the photos.
See Motion estimation and Correspondence problem
Daniel Cremers
Daniel Cremers (born 1971) is a German computer scientist, Professor of Informatics and Mathematics and Chair of Computer Vision & Artificial Intelligence at the Technische Universität München.
See Motion estimation and Daniel Cremers
Data compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation.
See Motion estimation and Data compression
Digital image processing
Digital image processing is the use of a digital computer to process digital images through an algorithm.
See Motion estimation and Digital image processing
Discrete cosine transform
A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies.
See Motion estimation and Discrete cosine transform
Film frame
In filmmaking, video production, animation, and related fields, a frame is one of the many still images which compose the complete moving picture.
See Motion estimation and Film frame
Graphics processing unit
A graphics processing unit (GPU) is a specialized electronic circuit initially designed for digital image processing and to accelerate computer graphics, being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles.
See Motion estimation and Graphics processing unit
High Efficiency Video Coding
High Efficiency Video Coding (HEVC), also known as H.265 and MPEG-H Part 2, is a video compression standard designed as part of the MPEG-H project as a successor to the widely used Advanced Video Coding (AVC, H.264, or MPEG-4 Part 10).
See Motion estimation and High Efficiency Video Coding
Image registration
Image registration is the process of transforming different sets of data into one coordinate system.
See Motion estimation and Image registration
Macroblock
The macroblock is a processing unit in image and video compression formats based on linear block transforms, typically the discrete cosine transform (DCT).
See Motion estimation and Macroblock
Motion
In physics, motion is when an object changes its position with respect to a reference point in a given time. Motion estimation and motion are motion (physics).
See Motion estimation and Motion
Motion compensation
Motion compensation in computing is an algorithmic technique used to predict a frame in a video given the previous and/or future frames by accounting for motion of the camera and/or objects in the video. Motion estimation and motion compensation are motion in computer vision.
See Motion estimation and Motion compensation
Moving object detection
Moving object detection is a technique used in computer vision and image processing. Motion estimation and Moving object detection are motion in computer vision.
See Motion estimation and Moving object detection
Moving Picture Experts Group
The Moving Picture Experts Group (MPEG) is an alliance of working groups established jointly by ISO and IEC that sets standards for media coding, including compression coding of audio, video, graphics, and genomic data; and transmission and file formats for various applications.
See Motion estimation and Moving Picture Experts Group
Optical flow
Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer and a scene. Motion estimation and Optical flow are motion in computer vision.
See Motion estimation and Optical flow
Phase correlation
Phase correlation is an approach to estimate the relative translative offset between two similar images (digital image correlation) or other data sets.
See Motion estimation and Phase correlation
Pixel
In digital imaging, a pixel (abbreviated px), pel, or picture element is the smallest addressable element in a raster image, or the smallest addressable element in a dot matrix display device.
See Motion estimation and Pixel
Random sample consensus
Random sample consensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers, when outliers are to be accorded no influence on the values of the estimates.
See Motion estimation and Random sample consensus
Scale-invariant feature transform
The scale-invariant feature transform (SIFT) is a computer vision algorithm to detect, describe, and match local features in images, invented by David Lowe in 1999.
See Motion estimation and Scale-invariant feature transform
Simultaneous localization and mapping
Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. Motion estimation and simultaneous localization and mapping are motion in computer vision.
See Motion estimation and Simultaneous localization and mapping
Taylor & Francis
Taylor & Francis Group is an international company originating in England that publishes books and academic journals.
See Motion estimation and Taylor & Francis
Video coding format
A video coding format (or sometimes video compression format) is a content representation format of digital video content, such as in a data file or bitstream.
See Motion estimation and Video coding format
Vision processing unit
A vision processing unit (VPU) is (as of 2023) an emerging class of microprocessor; it is a specific type of AI accelerator, designed to accelerate machine vision tasks.
See Motion estimation and Vision processing unit
Well-posed problem
In mathematics, a well-posed problem is one for which the following properties hold.
See Motion estimation and Well-posed problem
See also
Motion (physics)
- Absement
- Action (physics)
- Animal locomotion
- Bouncing ball
- Circular motion
- Complex harmonic motion
- Critical mass (sociodynamics)
- Curvilinear motion
- Displacement (geometry)
- Doppler velocity sensor
- Dynamics (mechanics)
- Kinematics
- Kinetic art
- Laws of motion
- Levitation
- Linear motion
- Lumino kinetic art
- Mobile (sculpture)
- Mobilities
- Momentum
- Motion
- Motion detector
- Motion estimation
- Motiongram
- Nouvelle tendance
- Principles of motion sensing
- Proper motion
- Robot locomotion
- Rolling cone motion
- Rotation
- Simple harmonic motion
- Velocity
- Waves
Motion in computer vision
- Activity recognition
- Horn–Schunck method
- Irissometry
- Kanade–Lucas–Tomasi feature tracker
- Lucas–Kanade method
- Lumitrack
- Match Analysis
- Match moving
- Motion analysis
- Motion capture
- Motion compensation
- Motion detection
- Motion estimation
- Motion field
- Moving object detection
- Object co-segmentation
- Optical flow
- Rigid motion segmentation
- Simultaneous localization and mapping
- Structure from motion
- Tomasi–Kanade factorization
- Velocity Moments
- Video content analysis
- Video motion analysis
- Video tracking
- Visual odometry
- Volumetric capture
- X-ray motion analysis
Video processing
- Deblocking filter
- Deflicking
- Deinterlacing
- Digital video fingerprinting
- Dream Machine (text-to-video model)
- Filter (video)
- Magisto
- Match moving
- Motion estimation
- Motion interpolation
- Scientific Working Group – Imaging Technology
- Shot transition detection
- Sora (text-to-video model)
- VDPAU
- Video acceleration
- Video compression
- Video denoising
- Video manipulation
- Video matting
- Video post-processing
- Video processing
- Xilleon
References
Also known as Algorithms for motion estimation, Feature based methods for motion estimation, Feature tracking, Motion vector, Pixel based methods for motion estimation.