Street Scene Video Anomaly Detection Dataset

Introduction The Street Scene dataset consists of 46 training video sequences and 35 testing video sequences taken from a static USB camera looking down on a scene of a two-lane street with bike lanes and pedestrian sidewalks. Videos were collected from the camera at various times during two consecutive summers. All of the videos were taken during the daytime. The dataset is challenging because of the variety of activities taking place such as cars driving, turning, stopping and parking; pedestrians walking, jogging and pushing strollers; and bikers riding in bike lanes. In addition, the videos contain changing shadows, and moving background such as a flag and trees blowing in the wind. There are a total of 202,545 color video frames (56,135 for training and 146,410 for testing) each of size 1280 x 720 pixels. The frames were extracted from the original videos at 15 frames per second. The 35 testing sequences have a total of 205 anomalous events consisting of 17 different anomaly types. A complete list of anomaly types and the number of each in the test set can be found in our paper. Ground truth annotations are provided for each testing video in the form of bounding boxes around each anomalous event in each frame. Each bounding box is also labeled with a track number, meaning each anomalous event is labeled as a track of bounding boxes. Track lengths vary from tens of frames to 5200 which is the length of the longest testing sequence. A single frame can have more than one anomaly labeled. NOTE: This version of the dataset differs slightly with the original made available in 2020. Some anomalies were found in a few of the normal training sequences. These training frames were deleted from the dataset. Specifically, the following frames were removed: Train026: frames 1-184 (car taking a u-turn) Train027: frames 1-229 (jay walkers) Train031: frames 1-299 (jay walkers, illegally parked car) At a Glance The size of the unzipped dataset is ~46GB The dataset consists of Train sequences (containing only videos with normal activity), Test sequences (containing some anomalous activity) along with ground truth annotations, and a README.md file describing the data organization and ground truth annotation format. The zip file contains a Train directory, a Test directory and a README.md file. Other Resources None Citation If you use the Street Scene dataset in your research, please cite our contribution: @inproceedings{ramachandra2020street,
title={Street Scene: A new dataset and evaluation protocol for video anomaly detection},
author={Ramachandra, Bharathkumar and Jones, Michael},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={2569--2578},
year={2020}
}
License The Street Scene dataset is released under CC-BY-SA-4.0 license. All data: Created by Mitsubishi Electric Research Laboratories (MERL), 2023

SPDX-License-Identifier: CC-BY-SA-4.0

数据集介绍
本街道场景（Street Scene）数据集包含46个训练视频序列与35个测试视频序列，数据由静态USB摄像头采集，拍摄视角为俯瞰一条带有自行车道与人行道的双向两车道街道。数据采集于连续两个夏季的不同日间时段。
本数据集具备较高挑战难度：场景内存在丰富多样的活动，包括车辆行驶、转向、停靠与驻车；行人步行、慢跑与推行婴儿车；骑行者在自行车道内通行。此外，视频中还包含动态变化的阴影，以及随风飘动的旗帜、树木等动态背景元素。
数据集总共有202,545张彩色视频帧，其中训练集含56,135帧，测试集含146,410帧，单帧分辨率为1280 × 720像素。所有视频帧以15帧每秒的速率从原始视频中提取。
35个测试序列中共包含205个异常事件，涵盖17种不同的异常类型。异常类型的完整列表及其在测试集中的数量分布可参见本团队的发表论文。
我们为每个测试视频提供了真值标注（ground truth annotation）：针对每一帧中的每个异常事件，均会生成对应的边界框（bounding box）；每个边界框还会标注跟踪编号（track number），即每个异常事件以边界框跟踪序列的形式进行标注。跟踪序列的长度从数十帧不等，最长可达5200帧（对应最长的测试序列长度）。单帧画面可同时标注多个异常事件。

> 注意：本数据集版本与2020年首次发布的原始版本存在细微差异。我们在少量正常训练序列中发现了异常样本，已将这些训练帧从数据集中移除。具体移除的帧如下：
> - Train026：第1~184帧（车辆掉头）
> - Train027：第1~229帧（行人乱穿马路）
> - Train031：第1~299帧（行人乱穿马路、非法停靠车辆）

概览
解压后的数据集大小约为46GB。数据集包含仅包含正常活动视频的训练序列、包含部分异常活动的测试序列，以及真值标注文件，同时附带一个README.md文件，用于说明数据组织方式与真值标注格式。压缩包内包含Train目录、Test目录与README.md文件。

其他资源
无

引用
若您在研究工作中使用本街道场景数据集，请引用如下文献：
bibtex
@inproceedings{ramachandra2020street,
title={Street Scene: A new dataset and evaluation protocol for video anomaly detection},
author={Ramachandra, Bharathkumar and Jones, Michael},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={2569--2578},
year={2020}
}

许可协议
本街道场景数据集采用CC-BY-SA-4.0许可协议发布。所有数据由三菱电机研究实验室（Mitsubishi Electric Research Laboratories, MERL）于2023年创建。
SPDX-License-Identifier: CC-BY-SA-4.0

搜集汇总

背景与挑战

背景概述

Street Scene Video Anomaly Detection Dataset是一个用于视频异常检测的数据集，包含46个训练视频和35个测试视频，总计超过20万帧街景视频，测试集中标注了205个异常事件和17种异常类型。数据集采集自静态摄像头拍摄的双车道街道场景，具有复杂的现实挑战，如多种交通参与者活动和动态背景变化，适用于开发和评估异常检测算法。