We present TIMo (Time-of-flight Indoor Monitoring), a dataset for video-based monitoring of indoor spaces captured using a time-of-flight (ToF) camera. The resulting depth videos feature people performing a set of different predefined actions, for which we provide detailed annotations. Person detection for people counting and anomaly detection are the two targeted applications. Most existing surveillance video datasets provide either grayscale or RGB videos. Depth information, on the other hand, is still a rarity in this class of datasets in spite of being popular and much more common in other research fields within computer vision. Our dataset addresses this gap in the landscape of surveillance video datasets. The recordings took place at two different locations with the ToF camera set up either in a top-down or a tilted perspective on the scene. The dataset is publicly available at https://vizta-tof.kl.dfki.de/timo-dataset-overview/.
翻译:我们介绍了利用飞行时间监测(ToF)相机对室内空间进行录像监测的数据集TIMO(飞行时空监测),由此产生的深度视频显示,人们执行一系列不同的预定行动,对此我们提供详细的说明;为计数和异常检测的人的探测是两个有针对性的应用程序;大多数现有的监视视频数据集提供灰度或RGB视频。另一方面,深度信息仍然是这一类数据集的罕见性,尽管在计算机视野的其他研究领域很受欢迎,而且更加常见。我们的数据集解决了监视视频数据集中的这一差距。录音是在两个不同地点拍摄的,托弗摄像机设置在自上而下或场面倾斜。数据集在https://vizta-tof.kl.dfki.de/timo-dataset-overview/上公开提供。