Video Analytics on IoT devices
This addresses the problem of selecting efficient video analytics methods for IoT devices, but it is incremental as it focuses on comparison rather than introducing new solutions.
The paper compares modern deep learning-based video analytics approaches with standard computer vision methods to determine the best-suited approach for IoT devices, but does not report specific results or numbers.
Deep Learning (DL) combined with advanced model optimization methods such as RC-NN and Edge2Train has enabled offline execution of large networks on the IoT devices. In this paper, we compare the modern Deep Learning (DL) based video analytics approaches with the standard Computer Vision (CV) based approaches and finally, discuss the best-suited approach for video analytics on IoT devices.