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Characterizing real-time dense point cloud capture and streaming on mobile devices
Point clouds are a dense compilation of millions of points that can advance content creation and interaction in various emerging applications such as Augmented Reality (AR). However, point clouds consist of per-point real-world spatial and color ...
Auto-SDA: Automated video-based social distancing analyzer
Social distancing can reduce infection rates in respiratory pandemics such as COVID-19, especially in dense urban areas. To assess pedestrians' compliance with social distancing policies, we use the pilot site of the PAWR COSMOS wireless edge-cloud ...
Decentralized modular architecture for live video analytics at the edge
Live video analytics have become a key technology to support surveillance, security, traffic control, and even consumer multimedia applications in real time. The continuous growth in number of networked video cameras will further increase their ...
Enabling high frame-rate UHD real-time communication with frame-skipping
With a high frame-rate and high bit-rate, ultra-high definition (UHD) real-time communication (RTC) users could sometimes suffer from severe service degradation. Due to the fluctuations of frames incoming and decoding at the client side, a decoder queue ...
The case for admission control of mobile cameras into the live video analytics pipeline
In this paper we consider the problem of orchestrating video analytics applications over an edge computing infrastructure. Video analytics applications have been traditionally associated to the processing of video streams generated by fixed video ...
Towards memory-efficient inference in edge video analytics
- Arthi Padmanabhan,
- Anand Padmanabha Iyer,
- Ganesh Ananthanarayanan,
- Yuanchao Shu,
- Nikolaos Karianakis,
- Guoqing Harry Xu,
- Ravi Netravali
Video analytics pipelines incorporate on-premise edge servers to lower analysis latency, ensure privacy, and reduce bandwidth requirements. However, compared to the cloud, edge servers typically have lower processing power and GPU memory, limiting the ...
Cost effective processing of detection-driven video analytics at the edge
We demonstrate a real-time video analytics system for applications that use objection detection models on incoming frames as part of their computation pipeline. Through edge-cloud collaboration, we show how a reinforcement learning based agent can skip ...