Video-based fast image set classification for IoT monitoring system

At present, the development of the Internet of Things (IoT) has become a significant symbol of the information age. And the video monitoring system is an important basic work in the IoT system. However, many existing video monitoring system usually use feature embedding method to learn more discriminative feature representation, while this manner is very time-consuming. And the learned features usually do not match the subsequent classifiers. To solve these issues, this paper proposes a new video-based fast image set classification framework, which consists of fast feature learning part and representation learning based classifier part. Extensive experiments on several well-known benchmark datasets demonstrate the effectiveness and efficiency of the proposed framework.