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  2. Reed–Solomon error correction - Wikipedia

    en.wikipedia.org/wiki/Reed–Solomon_error...

    Reed–Solomon codes are able to detect and correct multiple symbol errors. By adding t = n − k check symbols to the data, a Reed–Solomon code can detect (but not correct) any combination of up to t erroneous symbols, or locate and correct up to ⌊t/2⌋ erroneous symbols at unknown locations.

  3. Keystroke dynamics - Wikipedia

    en.wikipedia.org/wiki/Keystroke_dynamics

    Keystroke dynamics. Keystroke dynamics, keystroke biometrics, typing dynamics, or typing biometrics refer to the collection of biometric information generated by key-press-related events that occur when a user types on a keyboard. [1] Use of patterns in key operation to identify operators predates modern computing, [2] and has been proposed as ...

  4. Keystroke logging - Wikipedia

    en.wikipedia.org/wiki/Keystroke_logging

    Keystroke logging. Keystroke logging, often referred to as keylogging or keyboard capturing, is the action of recording (logging) the keys struck on a keyboard, [ 1][ 2] typically covertly, so that a person using the keyboard is unaware that their actions are being monitored. Data can then be retrieved by the person operating the logging program.

  5. Lucas–Kanade method - Wikipedia

    en.wikipedia.org/wiki/Lucas–Kanade_method

    Lucas–Kanade method. In computer vision, the Lucas–Kanade method is a widely used differential method for optical flow estimation developed by Bruce D. Lucas and Takeo Kanade. It assumes that the flow is essentially constant in a local neighbourhood of the pixel under consideration, and solves the basic optical flow equations for all the ...

  6. Kanade–Lucas–Tomasi feature tracker - Wikipedia

    en.wikipedia.org/wiki/Kanade–Lucas–Tomasi...

    In computer vision, the Kanade–Lucas–Tomasi (KLT) feature tracker is an approach to feature extraction. It is proposed mainly for the purpose of dealing with the problem that traditional image registration techniques are generally costly. KLT makes use of spatial intensity information to direct the search for the position that yields the ...

  7. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    Pyramids. v. t. e. 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. [ 1] Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual ...

  8. Perspective-n-Point - Wikipedia

    en.wikipedia.org/wiki/Perspective-n-Point

    Perspective-n-Point[ 1] is the problem of estimating the pose of a calibrated camera given a set of n 3D points in the world and their corresponding 2D projections in the image. The camera pose consists of 6 degrees-of-freedom (DOF) which are made up of the rotation (roll, pitch, and yaw) and 3D translation of the camera with respect to the world.

  9. Radar tracker - Wikipedia

    en.wikipedia.org/wiki/Radar_tracker

    A radar tracker is a component of a radar system, or an associated command and control (C2) system, that associates consecutive radar observations of the same target into tracks. It is particularly useful when the radar system is reporting data from several different targets or when it is necessary to combine the data from several different ...