Category : Computer Vision

Computer Vision Image Processing Publications Video Analysis

Video Quality Assessment (VQA)

The growing ubiquity of audiovisual content on the Internet has increased the importance of online advertising. With technological improvements, the quality of digital video rendering keeps improving as well, which in turn makes the users’ requirements stricter and stricter. So, the video quality is an important element to consider in online video advertising. Indeed, it goes without saying that a high quality video is more likely to interest users than a low quality video. Therefore it is crucial to be able to quantify the video’s quality. Nevertheless, the multiplicity of video formats and the various types of communication networks (wireless, fiber, xDSL networks…) make video quality assessment complex. Since the “end receiver” of video is human, the most accurate VQA is subjective (by humans). However, subjective assessment is time-consuming, and it depends on the person who evaluates it (mood, culture…). Thus, researchers have considered building objective assessment methods to model subjective methods. The advantage of objective VQA is that they can operate in real time. We will focus here on objective assessment processes for quality of video signals.

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Computer Vision Image Processing Information Retrieval Publications Video Analysis

Image Segmentation

Image segmentation aims at splitting an image into partitions. These partitions should usually represent some real part of the global image. This technique is used in object identification (Face recognition, or relevant information retrieval) in digital images. There are many different ways to perform image segmentation, such as image thresholding, region-based segmentation and Hough’s Transform.

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