SmartCamera: Realtime Video Stream-Oriented Action Recognition Platform in Edge Environment

Abstract

This paper designs a real-time video stream-oriented action recognition platform, namely SmartCamera. It aims to detect target actions in real-time in a resource-constrained edge environment. The SmartCamera adopts 3D convolutional network-based sliding window as the classification model of actions, and introduces a flexible sliding window localization method to reduce the computational complexity of action recognition without harming behavioral consistency. The prototype of SmartCamera mainly includes five modules: Real-time Video Stream Collection, Video Stream Preprocessing, Action Recognition, Sliding Window Localization, User Interface. The preliminary evaluation shows that the system can detect target actions with an acceptable accuracy and latency.