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The following is a simplistic illustrated explanation of how motion compensation works. Two successive frames were captured from the movie Elephants Dream.As can be seen from the images, the bottom (motion compensated) difference between two frames contains significantly less detail than the prior images, and thus compresses much better than the rest.
A frame grabber is an electronic device that captures (i.e., "grabs") individual, digital still frames from an analog video signal or a digital video stream. It is usually employed as a component of a computer vision system, in which video frames are captured in digital form and then displayed, stored, transmitted, analyzed, or combinations of ...
In inter-frame coding, individual frames of a video sequence are compared from one frame to the next, and the video compression codec records the differences to the reference frame. If the frame contains areas where nothing has moved, the system can simply issue a short command that copies that part of the previous frame into the next one.
Three types of pictures (or frames) are used in video compression: I, P, and B frames. An I‑frame (intra-coded picture) is a complete image, like a JPG or BMP image file. A P‑frame (Predicted picture) holds only the changes in the image from a previous frame. For example, in a scene where a car moves across a stationary background, only the ...
The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.
The points that correspond to each other in two views (images or frames) of a real scene or object are "usually" the same point in that scene or on that object. Before we do motion estimation, we must define our measurement of correspondence, i.e., the matching metric, which is a measurement of how similar two image points are.
MVC is based on the idea that video recordings of the same scene from multiple angles share many common elements. It is possible to encode all simultaneous frames captured in the same elementary stream and to share as much information as possible across the different layers. This can reduce the size of the encoded video. [5] [6]