Authentically Distorted Surveillance Videos Dataset

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. ------------------------------------------------------------------------------------------------------------------------------

本数据集包含在不同地点录制的“纯净”与“扭曲”视频。所采用的扭曲方式包括“聚焦”、“曝光”以及“聚焦+曝光”，三者分别以低（1）、中（2）和高（3）三个级别进行，共计形成10种条件（包括纯净视频）。此外，根据DIGIFORT软件中使用的H.264压缩格式，对扭曲视频进行了三种不同质量等级的导出，分别为：高质量（HQ，H.264 100%）、中质量（MQ，H.264 75%）和低质量（LQ，H.264 50%）。视频录制于半控制环境中，该环境具备促进真实扭曲视频生成的适宜环境条件。视频的管理与录制采用“DIGIFORT”监控系统软件完成。视频标注则使用“DarkLabel”标注软件进行。视频编辑与处理则借助“MATLAB”计算工具。数据集包含160个“纯净”视频、1450个“曝光”视频、1409个“聚焦”视频和1450个“聚焦+曝光”视频，总计4476个视频。记录的活动包括：“行走”（WL）、“在公共场所放置包裹”（LPP）、“通过”（PO）、“人推人”（PPP）、“人奔跑”（PR）、“群体斗殴”（FG）、“持刀抢劫”（RK）和“潜行”（PW）。本数据集旨在评估“视觉质量评估”（VQA）和“视觉目标跟踪”（VOT）算法。