LOST: Longterm Observation of Scenes (with Tracks)

Abstract

We introduce the Longterm Observation of Scenes (with Tracks) dataset. This dataset comprises videos taken from streaming outdoor webcams, capturing the same half hour, each day, for over a year. LOST contains rich metadata, including geolocation, day-by-day weather annotation, object detections, and tracking results. We believe that sharing this dataset opens opportunities for computer vision research involving very long-term outdoor surveillance, robust anomaly detection, and scene analysis methods based on trajectories. Efficient analysis of changes in behavior in a scene at very long time scale requires features that summarize large amounts of trajectory data in an economical way. We describe a trajectory clustering algorithm and aggregate statistics about these exemplars through time and show that these statistics exhibit strong correlations with external meta-data, such as weather signals and day of the week.