We describe VisFlow, a system that efficiently analyzes the feeds from many cameras.
Ubiquitous camera deployments are widely used for security, traffic monitoring, and …

Camera deployments are ubiquitous, but existing methods to analyze video feeds do not
scale and are error-prone. We describe Optasia, a dataflow system that employs relational …

Video cameras are pervasively deployed for security and smart city scenarios, with millions
of them in large cities worldwide. Achieving the potential of these cameras requires …

Many recent video applications---including traffic monitoring, drone analytics, autonomous
driving, and virtual reality---require piecing together, combining, and operating over many …

Recently, video database management systems (VDBMSs) have re-emerged as an active
area of research and development. To accelerate innovation in this area, we present Visual …

Pervasive deployment of surveillance cameras today poses enormous scalability challenges
to video analytics systems operating over many camera feeds. Currently, there are few …

Many recent video applications| including autonomous driving, traffic monitoring, drone
analytics, large-scale surveillance networks, and virtual reality require reasoning about …

Concerning the usability and efficiency to manage video data generated from large-scale
cameras, we demonstrate DoveDB, a declarative and low-latency video database. We …

State-of-the-art video database management systems (VDBMSs) often use lightweight proxy
models to accelerate object retrieval and aggregate queries. The key assumption underlying …

We present VStore, a data store for supporting fast, resource-efficient analytics over large
archival videos. VStore manages video ingestion, storage, retrieval, and consumption. It …