Networked Cameras Are the New Big Data Clusters
- Junchen Jiang ,
- Yuhao Zhou ,
- Ganesh Ananthanarayanan ,
- Yuanchao Shu ,
- Andrew A. Chien
Workshop on Hot Topics in Video Analytics and Intelligent Edges (HotEdgeVideo) |
With plummeting camera prices and increasing accuracy of deep neural networks (DNNs), we see an explosive growth of video-analytics applications over large camera deployments in the thousands, creating a multibillion dollar markets. Meanwhile, the proliferation of on-camera resource has spurred the prospect of massive live video analytics at edge. To deliver these promises, however, we must address the fundamental systems challenge: How to use on-camera resource in a large fleet of cameras to run more video-analytics applications?
Microsoft Rocket: Hybrid Edge + Cloud Video Analytics Platform
Today, video cameras are being used at a large scale by public and private enterprises for a variety of reasons—from security surveillance and traffic planning to consumer support in retail and hospitality settings. Thanks to gains in computer vision, particularly object detection and classification, video analysis has become more accurate. Fast and affordable real-time analysis, however, is lagging. Project Rocket seeks to make easy, cost-effective video analysis of live camera streams a reality. Project Rocket, an extensible software stack that leverages the edge and cloud, is designed with maximum functionality in mind, capable of meeting the needs of varying video analytic applications. In this webinar, Microsoft researchers Ganesh Ananthanarayanan and Yuanchao Shu explain how Rocket—now open source on GitHub—uses approximation to run scalable analytics across…