Real-time video analytics on small autonomous drones poses several difficult challenges at the intersection of wireless bandwidth, processing capacity, energy consumption, result accuracy, and timeliness of results. In response to these challenges, we describe four strategies to build an adaptive computer vision pipeline for search tasks in domains such as
The generation of high-quality training data has become the key bottleneck in the use of deep learning across many domains. We describe Eureka, an interactive system that leverages edge computing and early discard to greatly improve the productivity of experts in the construction of a labeled data set. Our experimental
Recently, edge computing has emerged as a promising computing paradigm to meet stringent quality-of-service requirements of an increasing number of latency-sensitive applications. The core principle of edge computing is to bring the capability of cloud computing in close proximity to mobile devices, sensors, actuators, connected things and end users, thereby
Wearable cognitive assistance applications can provide guidance for many facets of a user’s daily life. This thesis targets the enabling of a new genre of such applications that require both heavy computation and very low response time on inputs from mobile devices. The core contribution of this thesis is
Accurate, up-to-date maps of transient traffic and hazards are invaluable to drivers, city managers, and the emerging class of self-driving vehicles. We present LiveMap, a scalable, automated system for acquiring, curating, and disseminating detailed, continually-updated road conditions in a region. LiveMap leverages in-vehicle cameras, sensors, and processors to crowd-source hazard
VM handoff enables rapid and transparent placement changes to executing code in edge computing use cases where the safety and management attributes of VM encapsulation are important. This versatile primitive offers the functionality of classic live migration but is highly optimized for the edge. Over WAN bandwidths ranging from 5
An emerging class of interactive wearable cognitive assistance applications is poised to become one of the key demonstrators of edge computing infrastructure. In this paper, we design seven such applications and evaluate their performance in terms of latency across a range of edge computing configurations, mobile hardware, and wireless networks,
Computer vision based technologies have seen widespread adoption over the recent years. This use is not limited to the rapid adoption of facial recognition technology but extends to facial expression recognition, scene recognition and more. These developments raise privacy concerns and call for novel solutions to ensure adequate user awareness,
Situational awareness involves the timely acquisition of knowledge about real-world events, distillation of those events into higher-level conceptual constructs, and their synthesis into a coherent context-sensitive view. We explore how convergent trends in video sensing, crowd sourcing and edge computing can be harnessed to create a shared real-time information system
We present OpenFace, our new open-source face recognition system that approaches state-of-the-art accuracy. Integrating OpenFace with inter-frame tracking, we build RTFace, a mechanism for denaturing video streams that selectively blurs faces according to specified policies at full frame rates. This enables privacy management for live video analytics while providing a
As video cameras proliferate, the ability to scalably capture and search their data becomes important. Scalability is improved by performing video analytics on cloudlets at the edge of the Internet, and only shipping extracted index information and meta-data to the cloud. In this setting, we describe interactive data exploration (IDE)
OEC Admin