Date of Original Version
Abstract or Description
Event reconstruction is about reconstructing the event truth from a large amount of videos which capture different moments of the same event at different positions from different perspectives. Up to now, there are no related public datasets. In this paper, we introduce the first real-world event reconstruction dataset to promote research in this field. We focus on synchronization and localization, which are the two basic and essential elements for other tasks in event reconstruction such as person tracking, scene reconstruction, and object retrieval. It covers 347 original videos and 1, 066 segmented clips of the real-world event of the explosions at the 2013 Boston Marathon finish line. We provide high precision ground truth labels for localization and two granularity ground truth labels for synchronization on 109 clips. We derive several metrics on video level and frame level to evaluate the two tasks. We also provide auxiliary data including video comments with timestamp, map meta data, environment images, and a 3d point cloud which are helpful for the synchronization and the localization tasks. Finally, we position our dataset as a real-world test dataset, without limiting the usage of extra training data.
The dataset is released at http://aladdin1.inf.cs. cmu.edu:8081/boston