Abnormal Event Detection in Videos using Spatiotemporal Autoencoder

Understand

We present an efficient method for detecting anomalies in videos.

• Recent applications of convolutional neural networks have shown promises of convolutional layers for object detection and recognition, especially in images.
• However, convolutional neural networks are supervised and require labels as learning signals.
• We propose a spatiotemporal architecture for anomaly detection in videos including crowded scenes.