Video surveillance systems
When selecting a video surveillance
Uses a systems approach rather than a components approach
Video surveillance systems
The following parameters determine the effectiveness of a video assessment subsystem
Parameters Ctd…
Video Surveillance
3 reasons for cameras in security applications
Video Surveillance
Primary uses of video surveillance systems
Detection of Activities
Recording of Incidents
Assessment of Alarms/Incidents
Video Surveillance
Main elements of video surveillance systems
Field of View (FOV)
Scene
Lens
Camera (including mounting hardware)
Transmission Medium
Monitor
Recording Equipment (analog/digital)
Control Equipment
Video Surveillance
Three main components of an analog video surveillance system
Camera
Transmission Cable
Monitor
Video Surveillance
3 main components of a digital video surveillance system
Camera
Digital electronic signal center
PC with software
Video Surveillance
In designing a video surveillance application security managers should keep in mind
Designing Video Surveillance Ctd…
No matter what, the equipment of the system will become obsolete
Key points for designing VS systems
Video Surveillance
Simple Rules For Design
Keep system in perspective
Design generically
Design for best options first (budget after)
Don’t feel driven to build the system all at once
Video Surveillance
Steps for design
Video Surveillance
Resolution is determined by the following in order
Limiting Factors
- DVR’s digitize analog signals, dropping 25% of the resolution
- Sloppy installation or cheap coaxial cable costs 10 - 15% resolution
Video Surveillance
All IP cameras measure resolution as a multiple of the Common Intermediate Format (CiF) about half the average 325 horizontal lines; not recommended as a usable standard for storage
3 Considerations when determining video surveillance field & view (FOV)
Target (person, vehicles, etc…)
Activity (assault, slight of hand)
Purpose (identification vs. general monitoring)
Video surveillance systems are designed to be only two things
Visual assessment (what’s happening now)
Visual documentation (What happened previously)
3 Theoretical identification views of an analog VSS
1. Subject identification
2. Action identification
3. Scene identification
VS - Fields of view (FOV)
Theoretical identification views of a digital VSS
General: Can’t distinguish clothing & color - pixelated zoom (5 pix/ft)
Monitor: General vehicle/human traffic flows - no serious detail on zoom (7 pix/ft)
Detect: Detect but not identify person-sized object - no significant detail on zoom (4 pix/ft)
Observe: Clothing/colors gain distinction - no good detail on zoom (18 pix/ft)
Recognize: High degree of accuracy identifying & separating known individuals - good detail on zoom (35 pix/ft)
ID views of a digital VSS
Subject ID: Establish identity beyond a shadow of a doubt - the excellent detail on zoom (48 pix)
License Plat ID: ID of license plates - excellent detail on zoom (70 pix)
Facial Recog: Extreme details - excellent detail on zoom (88 pix)
VS - FOV
Identification of an object in video means…
The ability to differentiate between people’s identity
VS - FOV
Classification of an object in video means…
The ability to differentiate between humans animals etc…
VS - FOV
Cameras should not be required to view more than one major and one more minor objective