  Low-cost cameras enable powerful analytics. An unexploited opportunity is
that most captured videos remain "cold" without being queried. For efficiency,
we advocate for these cameras to be zero streaming: capturing videos to local
storage and communicating with the cloud only when analytics is requested. How
to query zero-streaming cameras efficiently? Our response is a camera/cloud
runtime system called DIVA. It addresses two key challenges: to best use
limited camera resource during video capture; to rapidly explore massive videos
during query execution. DIVA contributes two unconventional techniques. (1)
When capturing videos, a camera builds sparse yet accurate landmark frames,
from which it learns reliable knowledge for accelerating future queries. (2)
When executing a query, a camera processes frames in multiple passes with
increasingly more expensive operators. As such, DIVA presents and keeps
refining inexact query results throughout the query's execution. On diverse
queries over 15 videos lasting 720 hours in total, DIVA runs at more than 100x
video realtime and outperforms competitive alternative designs. To our
knowledge, DIVA is the first system for querying large videos stored on
low-cost remote cameras.
