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Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Video Fields: Fusing Multiple Surveillance Videos into a
Dynamic Virtual Environment
Ruofei Du, Sujal Bista, Amitabh Varshney
The Augmentarium| UMIACS | University of Maryland, College Park
{ruofei, sujal, varshney} @ cs.umd.edu
www.VideoFields.com
image courtesy: university of maryland, college park
Introduction
Surveillance Videos - Monitoring
image courtesy: www.icsc.org
Introduction
Surveillance Videos – Shopping Centers
image courtesy: wikipedia
Introduction
Surveillance Videos - Airports
image courtesy: wikipedia
Introduction
Surveillance Videos – Train stations
image courtesy: university of maryland, college park
Introduction
Surveillance Videos - Campuses
image courtesy: university of maryland, college park
Introduction
Surveillance Videos - Conventional
image courtesy: theimaginativeconservative.org
Introduction
Surveillance Videos – Cognitive Burden
image courtesy: university of maryland, college park
Introduction
Surveillance Videos – Fusing & Interpreting
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Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
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SIGGRAPH 2016
Wednesday, 3:30-4:00 PM
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Our Approach?
Video Fields
Video Fields
Introduction
Video Field
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Introduction
Video Field
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Conception, architecting & implementation
Video Fields
A mixed reality system that fuses multiple
surveillance videos into an immersive virtual
environment,
Integrating automatic segmentation of
moving entities
Video Fields Rendering
Real-time fragment shader processing
Two algorithms to fuse multiple videos
Early & deferred pruning
These methods use voxels and meshes respectively
to render moving entities in the video fields
Achieving cross-platform compatibility by
WebGL + Three.js
smartphones, tablets, desktop, high-resolution
large-area wide field of view tiled display walls, as
well as head-mounted displays.
System Overview
Architecture
Video Fields Flowchart
Architecture
Video Fields Flowchart
Architecture
Video Fields Flowchart
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Architecture
Video Fields Flowchart
Background Modeling
Motivation
• Provide a background texture for each camera
• Identify moving entities in the rendering stage
• Reduce the network bandwidth requirements
Background Modeling
Gaussian Mixture Models (GMM)
Background Modeling
Advantages [Stauffer and Grimson]
More adaptive with:
• different lighting conditions,
• repetitive motions of scene elements,
• moving entities in slow motion
Architecture
Video Fields Flowchart
Segmentation
Moving Entities
Background Modeling
Gaussian Mixture Models (GMM)
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Architecture
Video Fields Flowchart
Visibility Test
Plus Opacity Modulation
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Architecture
Video Fields Flowchart
Video Fields Mapping
Overview
Video Fields Mapping
Challenges
1. Vertex in the 3D models -> Pixel in the texture space
2. Pixel in the texture space -> Vertex on the ground
• The second is useful for projecting a 2D segmentation
of a moving entity to the 3D world
Video Fields Mapping
Projection Mapping
Video Fields Mapping
Perspective correction
Video Fields Mapping
Depth Map / Hashing Function
Early Pruning for Rendering
Moving Entities
Voxels
Deferred Pruning for
Rendering Moving Entities
Billboards
Visual Comparison
Early Pruning vs. Deferred Pruning
View-dependent Rendering
View-dependent Rendering
View-dependent Rendering
View-dependent Rendering
Experimental Results
Early Pruning vs. Deferred Pruning
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Experimental Results
Early Pruning vs. Deferred Pruning
Experimental Results
Early Pruning vs. Deferred Pruning
Visual Comparison
Early Pruning vs. Deferred Pruning
Video Fields: Fusing Multiple Surveillance Videos into a Dynamic Virtual Environment
Future Work
Scale Up - Hundreds of cameras
Future Work
Bandwidth Problem
Future Work
Holoportation with RGB cameras
Acknowledgement
Augmentarium Lab | GVIL | UMIACS
Acknowledgement
NSF | Nvidia | MPower | UMIACS
Video Fields
www.Video-Fields.com
Thank you! Questions or comments?
Ruofei Du and Amitabh Varshney
Augmentarium Lab | GVIL | UMIACS
Web3D 2016

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