enow.com Web Search

  1. Ad

    related to: computer vision algorithms and applications python course

Search results

  1. Results from the WOW.Com Content Network
  2. Computer vision - Wikipedia

    en.wikipedia.org/wiki/Computer_vision

    Computer vision is an 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.

  3. Avinash Kak - Wikipedia

    en.wikipedia.org/wiki/Avinash_Kak

    The SART algorithm [8] (Simultaneous Algebraic Reconstruction Technique) proposed by Andersen and Kak in 1984 has had a major impact in CT imaging applications where the projection data is limited. As a measure of its popularity, researchers have proposed various extensions to SART: OS-SART, FA-SART, VW-OS-SART, SARTF, etc. Researchers have ...

  4. Simultaneous localization and mapping - Wikipedia

    en.wikipedia.org/wiki/Simultaneous_localization...

    SLAM algorithms are based on concepts in computational geometry and computer vision, and are used in robot navigation, robotic mapping and odometry for virtual reality or augmented reality. SLAM algorithms are tailored to the available resources and are not aimed at perfection but at operational compliance.

  5. Scale-invariant feature transform - Wikipedia

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

    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 identification of ...

  6. Bundle adjustment - Wikipedia

    en.wikipedia.org/wiki/Bundle_adjustment

    In photogrammetry and computer stereo vision, bundle adjustment is simultaneous refining of the 3D coordinates describing the scene geometry, the parameters of the relative motion, and the optical characteristics of the camera(s) employed to acquire the images, given a set of images depicting a number of 3D points from different viewpoints.

  7. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    Connected-component labeling is used in computer vision to detect connected regions in binary digital images, although color images and data with higher dimensionality can also be processed. [ 1 ] [ 2 ] When integrated into an image recognition system or human-computer interaction interface, connected component labeling can operate on a variety ...

  8. Viola–Jones object detection framework - Wikipedia

    en.wikipedia.org/wiki/Viola–Jones_object...

    The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes.

  9. Harris corner detector - Wikipedia

    en.wikipedia.org/wiki/Harris_corner_detector

    The Harris corner detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image. It was first introduced by Chris Harris and Mike Stephens in 1988 upon the improvement of Moravec's corner detector. [1]

  1. Ad

    related to: computer vision algorithms and applications python course