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Authentically Distorted Surveillance Videos Dataset

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IEEE2020-05-07 更新2026-04-17 收录
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https://ieee-dataport.org/open-access/authentically-distorted-surveillance-videos-dataset
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This Dataset contains Pristine and Distorted videos recorded in different places. The distortions with which the videos were recorded are: Focus, Exposure and Focus + Exposure. Those three with low (1), medium (2) and high (3) levels, forming a total of 10 conditions (including Pristine videos). In addition, distorted videos were exported in three different qualities according to the H.264 compression format used in the DIGIFORT software, which were: High Quality (HQ, H.264 at 100%), Medium Quality (MQ, H.264 at 75%) and Low Quality (LQ, H.264 at 50%).The recording of the videos was carried out in a semicontrolled space, with the appropriate environment conditions that facilitate the generation of authentically distorted videos. The DIGIFORT monitoring software is used to manage and record the videos. For the labeling of each video we use the DarkLabel labeling software. For the videos editing and processing the MATLAB computational tool is used. The dataset contains 160 Pristine videos, 1450 Exposure videos, 1409 Focus videos and 1450 Focus + Exposure videos for a total of 4476 videos. The recorded activities are: Walking (WL), Leaving Package in a Public Place (LPP), Passing Out (PO), Person Pushing Person (PPP), Person Running (PR), Fighting in Group (FG), Robbery with Knife (RK) and Prowl (PW). This Dataset is intended to evaluate Visual Quality Assessment (VQA) and Visual Object Tracking (VOT) algorithms. ------------------------------------------------------------------------------------------------------------------------------
提供机构:
Bonilla Vergara, Santiago Nicolás; Ardila Franco, César Augusto; Benítez Restrepo, Hernán Darío; Gómez Nieto, Roger Alfonso
创建时间:
2020-05-07
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