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Video quality is a characteristic of a video passed through a video transmission or processing system that describes perceived video degradation (typically compared to the original video). Video processing systems may introduce some amount of distortion or artifacts in the video signal that negatively impact the user's perception of the system.
Video management software manufacturers are constantly expanding the range of the video analytics modules available. With the new suspect tracking technology, it is then possible to track all of this subject's movements easily: where they came from, and when, where, and how they moved.
Online video analytics (also known as Web video analytics) is the measurement, analysis and reporting of videos viewed online. It is used for the purposes of understanding the consumption patterns ( behavioral analysis ) and optimizing viewing experience ( quality of service analysis).
The development for picture quality analysis algorithms available today started with still image models which were later enhanced to also cover motion pictures. PEVQ is full-reference algorithm (see the classification of models in video quality ) and analyzes the picture pixel-by-pixel after a temporal alignment (also referred to as 'temporal ...
See also, the Motion topic for video quality requirements considerations. [3] Motion Picture Expert Group (MPEG) A group of standards for encoding and compressing audiovisual information such as movies, video, and music. MPEG compression is as high as 200:1 for low-motion video of VHS quality, and broadcast quality can be achieved at 6 Mbit/s.
The structural similarity index measure (SSIM) is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. It is also used for measuring the similarity between two images.
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The metric is based on initial work from the group of Professor C.-C. Jay Kuo at the University of Southern California. [1] [2] [3] Here, the applicability of fusion of different video quality metrics using support vector machines (SVM) has been investigated, leading to a "FVQA (Fusion-based Video Quality Assessment) Index" that has been shown to outperform existing image quality metrics on a ...