Focus: Querying Large Video Datasets with Low Latency and Low Cost

01/10/2018
by   Kevin Hsieh, et al.
0

Large volumes of videos are continuously recorded from cameras deployed for traffic control and surveillance with the goal of answering "after the fact" queries: identify video frames with objects of certain classes (cars, bags) from many days of recorded video. While advancements in convolutional neural networks (CNNs) have enabled answering such queries with high accuracy, they are too expensive and slow. We build Focus, a system for low-latency and low-cost querying on large video datasets. Focus uses cheap ingestion techniques to index the videos by the objects occurring in them. At ingest-time, it uses compression and video-specific specialization of CNNs. Focus handles the lower accuracy of the cheap CNNs by judiciously leveraging expensive CNNs at query-time. To reduce query time latency, we cluster similar objects and hence avoid redundant processing. Using experiments on video streams from traffic, surveillance and news channels, we see that Focus uses 58X fewer GPU cycles than running expensive ingest processors and is 37X faster than processing all the video at query time.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/04/2020

SurveilEdge: Real-time Video Query based on Collaborative Cloud-Edge Deep Learning

The real-time query of massive surveillance video data plays a fundament...
research
06/21/2021

Boggart: Accelerating Retrospective Video Analytics via Model-Agnostic Ingest Processing

Delivering fast responses to retrospective queries on video datasets is ...
research
04/28/2019

Supporting Video Queries on Zero-Streaming Cameras

As low-cost surveillance cameras grow rapidly, we advocate for these cam...
research
12/13/2022

Query Time Optimized Deep Learning Based Video Inference System

This is a project report about how we tune Focus[1], a video inference s...
research
06/11/2018

Physical Representation-based Predicate Optimization for a Visual Analytics Database

Querying the content of images, video, and other non-textual data source...
research
03/07/2017

NoScope: Optimizing Neural Network Queries over Video at Scale

Recent advances in computer vision-in the form of deep neural networks-h...
research
05/19/2020

ExSample: Efficient Searches on Video Repositories through Adaptive Sampling

Capturing and processing video is increasingly common as cameras become ...

Please sign up or login with your details

Forgot password? Click here to reset