Computer Vision Examples

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Computer vision
Name:A.Saravanan
Class:III BCA ‘A’
College:K.C.S.KasiNadar College of Arts and Science
Abstract:
Computer vision is an area that consists method for acquiring,processing,analyzing and understanding images from the real world in order to produce numerical or symbolic information. Computer vision has described as the enterprise of automating and integrating a wide range of processes and representations for vision perception.Let us discuss about characteristics,Applications,typical tasks,recognition,motion analysis, and computer vision methods are discussed below. Characteristics:
The following characterizations appear relevant but should not be taken as universally accepted:
Computer vision includes 3D analysis from 2D images.
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The computer vision and machine vision fields have significant overlap. Computer vision covers the core technology of automated image analysis which is used in many fields. Machine vision usually refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in industrial applications. In many computer vision applications, the computers are pre-programmed to solve a particular task, but methods based on learning are now becoming increasingly common. Examples of applications of computer vision include systems…show more content…
ASCII).
Facial Recognition:Shape Recognition Technology (SRT) is used to change the facial expression of the person especiially head and shoulder patterns.
Motion analysis
Several tasks relate to motion estimation where an image sequence is processed to produce an estimate of the velocity either at each points in the image or in the 3D scene, or even of the camera that produces the images . Examples of such tasks are:
Egomotion – determining the 3D rigid motion (rotation and translation) of the camera from an image sequence produced by the camera.
Tracking – following the movements of a (usually) smaller set of interest points or objects (e.g., vehicles or humans) in the image sequence.
Optical flow – to determine, for each point in the image, how that point is moving relative to the image plane, i.e., its apparent motion. This motion is a result both of how the corresponding 3D point is moving in the scene and how the camera is moving relative to the scene.
Computer vision system

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