Anomaly recognition from surveillance videos using 3D convolution neural network

Anomalous activity recognition deals with identifying the patterns and events that vary from the normal stream. In a surveillance paradigm, these events range from abuse to fighting and road accidents to snatching, etc. Due to the sparse occurrence of anomalous events, anomalous activity recognition from surveillance videos is a challenging research task. The approaches reported can be generally categorized as handcrafted and deep learning-based.

Keywords: Anomalous activity recognition, 3DConvNets, spatial augmentation, spatial annotation

• Authors: Ramna Maqsood, Usama Ijaz Bajwa, Gulsha Saleem, Rana Hammad Raza
• Date: February 2021
• Link: Read Paper