Publications

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)

Industry investment and research interest in edge computing, in which computing and storage nodes are placed at the Internet's edge in close proximity to mobile devices or sensors, have grown dramatically in recent years. This emerging technology promises to deliver highly responsive cloud services for mobile computing, scalability and privacy-policy

The convergence of mobile computing and cloud computing enables new mobile applications that are both resource-intensive and interactive. For these applications, end-to-end network bandwidth and latency matter greatly when cloud resources are used to augment the computational power and battery life of a mobile device. This dissertation designs and implements

Computational offloading services at the edge of the Internet for mobile devices are becoming a reality. Using a wide range of mobile applications, we explore how such infrastructure improves latency and energy consumption relative to the cloud. We present experimental results from WiFi and 4G LTE networks that confirm substantial

Cyber-foraging is a technique to enable mobile devices to extend their computing power and storage by offloading computation or data to more powerful servers located in the cloud, or to proximate servers called surrogates. There are two main forms of cyber-foraging. One is computation offload, which is the offload of

Cameras are becoming ubiquitous in the Internet of Things (IoT) and can use face recognition technology to improve context. There is a large accuracy gap between today’s publicly available face recognition systems and the state-of-the-art private face recognition systems. This paper presents our OpenFace face recognition library that bridges

We show how a disruptive force in mobile computing can be created by extending today's unmodified cloud to a second level consisting of self-managed data centers with no hard state called cloudlets. These are located at the edge of the Internet, just one wireless hop away from associated mobile devices.

We describe the architecture and prototype implementation of an assistive system based on Google Glass devices for users in cognitive decline. It combines the first-person image capture and sensing capabilities of Glass with remote processing to perform real-time scene interpretation. The system architecture is multi-tiered. It offers tight end-to-end latency