In this paper, we investigate the optimal configuration and dependence-aware task
assignment for multi-task edge video analytics. Multi-task video analytics involves multiple …

With the development of artificial intelligence technology and intelligent devices, people
show great interest in intelligent applications and services, but it is impossible to complete …

With the advancements in Machine Learning (ML) and edge computing, increasing efforts
have been devoted to edge video analytics. However, most of the existing works fail to …

Camera-based monitoring is becoming increasingly popular, as multi-objective detection
tasks can be enabled by video analytics over captured frames. Yet, video frames have to be …

Video analysis typically requires a significant amount of computing resources and energy.
Traditional cloud-based video analysis relies on concentrating computing resources in the …

Edge computing has opened new doors for real-time video analytics applications due to its
ability to offer significantly faster response times by processing videos near the source …

Edge-assisted video analytics is gaining momentum. In this work, we tackle an important
problem to compress video content live streamed from the device to the edge without …

With the popularization of visual machine learning, intelligent video analytics can
automatically analyze and extract information from video streams, yet it brings heavy …

Reliable object detection is essential for smart surveillance systems, and video surveillance
technology has been significantly improved thanks to Deep-Learning related techniques …

Deep learning-based video analytics is computation-intensive. Manufacturers such as
Nvidia have launched many embedded deep learning accelerators and are rapidly gaining …