1. Three-Dimensionalizing Surveillance Networks
James Elder, Project Leader
York University

2. The challenge
To use persistent visual surveillance data to maintain and improve the security and efficiency of our urban centres in the face of rapid growth and increasing complexity

3. Current obstacles
Most surveillance data are ignored due to lack of adequate manpower and reliable visual algorithms.
Persistent visual surveillance systems are poorly integrated with other forms of geospatial information
Surveillance cams compress the 3D scene into 2D, making inference difficult

4. Example (real, but anonymous public institution)
400 cameras
8 monitors
2 vigilant
undergraduates
What if something happens?

5. What if something happens?

6. A better way

7. Street level

8. Street Level

9. Goals
Automatic, efficient, scaleable methods for extraction and integration of 2D and 3D urban data at street level
Surveillance video, UAV photogrammetry, airborne & terrestrial LIDAR…
Automatic inference of 3D scene properties
Scene segmentation, building characteristics, foliage modeling
Automatic inference of 3D scene dynamics
Human and pedestrian traffic
Integrated reporting and 3D visualization
For efficient human interpretation
Integration into distributed software architecture
CAE S-Mission architecture

10. Scientific Questions There are many, e.g.,
How can 3D urban scene information be reliably extracted from single-view video?
How can individuals be discriminated in crowds?
How can free-form structures (e.g., trees) be reliably segmented from the scene?
How can multiple forms of geolocation data (GPS, inertial, visual) be integrated to optimize positioning?

11. Applications Public and private security Urban planning
Business analytics

12. Academic Team Claire Samson Carleton Frank Ferrie McGill Jim Little
UBC
Ayman Habib
Calgary
Dave Clausi
John Zelek
Waterloo
York
James Elder
Gunho Sohn

13. Associated Korean Land Spatialization Group Projects
Project 1. Real-time Aerial Monitoring System
Project Leader: Impyeong Lee, Head, Dept. of Geoinformatics, The University of Seoul
Project 2. Mobile Mapping at Street Level
Project Leader: Taejung Kim, Associate Professor, Dept. of Geoinformatic Engineering, Inha University

14. Partners: 3D Modeling and Mapping

15. City of Toronto Survey & Mapping Services
2D and 3D mapping and modeling
Asset management
Bylaw enforcement

16. Defence Research & Development Canada
3D automatic target detection & recognition

17. CAE 3D modeling and simulation 3D immersive visualization
Distributed real-time systems

18. Presagis
COTS 3D modeling and simulation products

19. Applanix
Mobile mapping and positioning
GPS + Inertial + Visual

20. Array Systems 3D LIDAR scanning and modeling
Scaleable signal processing systems

21. dmti Spatial
Location-based data and services

22. Partners: Scene Dynamics

23. Ministry of Transport Ontario
COMPASS Highway Surveillance Network

24. Honeywell Video Systems
Intelligent visual systems for surveillance and business analytics
People and object tracking
Face detection
Crowd density measurements

25. Aimetis Intelligent video surveillance systems Infrastructure
Transportation
Retail

26. Miovision
Automated traffic flow analysis

27. Aeryon Labs
Small electric UAVs for visual surveillance

28. For more on the project…
Kick-off workshop Saturday 9-5 in King George Room: feel free to drop in.