1. Anomaly Detection in Satellite Videos using Diffusion Models
- Author
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Awasthi, Akash, Ly, Son, Nizam, Jaer, Zare, Samira, Mehta, Videet, Ahmed, Safwan, Shah, Keshav, Nemani, Ramakrishna, Prasad, Saurabh, and Van Nguyen, Hien
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
The definition of anomaly detection is the identification of an unexpected event. Real-time detection of extreme events such as wildfires, cyclones, or floods using satellite data has become crucial for disaster management. Although several earth-observing satellites provide information about disasters, satellites in the geostationary orbit provide data at intervals as frequent as every minute, effectively creating a video from space. There are many techniques that have been proposed to identify anomalies in surveillance videos; however, the available datasets do not have dynamic behavior, so we discuss an anomaly framework that can work on very high-frequency datasets to find very fast-moving anomalies. In this work, we present a diffusion model which does not need any motion component to capture the fast-moving anomalies and outperforms the other baseline methods.
- Published
- 2023