Surveillance footage for activity analysis in complicated scenes

This dataset, the SAIVT-Campus Database is an abnormal event detection database captured at the Queensland University of Technology, Australia. It contains two video files from real world surveillance footage without any actors. Each video file is one hour in duration. The normal activities include pedestrians entering or exiting the building, entering or exiting a lecture theatre (yellow door), and going to the counter at the bottom right. The abnormal events are caused by a heavy rain outside, and include people running in from the rain, people walking towards the door to exit and turning back, wearing raincoats, loitering and standing near the door and overcrowded scenes. The rain happens only in the later part of the test dataset. As a result, we assume that the training dataset only contains the normal activities.

该数据集，即 SAIVT-Campus 数据库，为澳大利亚昆士兰科技大学捕获的异常事件检测数据库。该数据库包含来自现实世界监控录像的两组视频文件，且视频中无任何演员参与。每段视频文件时长为一小时。正常活动包括行人进出建筑、进入或离开报告厅（黄色大门），以及前往位于右下角的柜台。异常事件由外部暴雨引起，包括人们在雨中奔跑、走向门口准备离开后又折返、穿着雨衣、闲逛以及聚集在门口的拥挤场景。暴雨仅出现在测试数据集的后半部分。因此，我们假设训练数据集仅包含正常活动。