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Associated SPS Event: IEEE ICIP 2022 Grand Challenge
The perceptual quality of images/videos in the context of video surveillance has a very significant impact on high-level tasks such as object detection, identification of abnormal events, visual tracking, to name a few. Despite the development of advanced video sensors with higher resolution, the quality of the acquired video is often affected by some distortions due to the environment, encoding and storage technologies, which can only be avoided by employing of intelligent post-processing solutions. It is then necessary to develop methods to detect and identify the different degradations to apply the appropriate quality enhancement processing. Another major difficulty not often considered in video quality enhancement studies is the case of multiple distortions that affect the signal simultaneously. The database presented here includes this real problem. It is indeed essential to identify the elements of the distortion mixture in order to apply the most appropriate quality enhancement solutions. In order to complete this challenge, we will provide our dataset of short-duration surveillance videos called the Video Surveillance Quality Assessment Dataset (VSQuAD). The database consists of original videos recorded by the team members and other sequences selected from public databases. These videos are degraded artificially with various types of distortions (single or simultaneous) at different levels.
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