Vicon Valerus SmartAnalytics User guide

Vicon
Brand
Vicon
Model
Valerus SmartAnalytics
Category
Security cameras
Type
User guide
ValerusV Valerus SmartAnalytics
User Best Practices Guide
XX306-20-00
Vicon Industries Inc. does not warrant that the functions contained in this equipment
will meet your requirements or that the operation will be entirely error free or
perform precisely as described in the documentation. This system has not been
designed to be used in life-critical situations and must not be used for this purpose.
Document Number: 8009-8306-20-00 Product specifications subject to change
without notice. Issued: 9/18 Copyright © 2018 Vicon Industries Inc. All rights
reserved.
Vicon Industries Inc.
Tel: 631-952-2288)
Fax: 631-951-2288
Toll Free: 800-645-9116
24-Hour Technical Support:
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www.vicon-security.com
Best Practices Guide
August 2018
Table of Contents
1 Introduction ......................................................................................................... 4
2 Performing a Site Survey ................................................................................... 4
3 Verifying Valerus SmartAnalytics Products Deployment Requirements ....... 5
3.1 Real-time Video Analysis and Alerts ................................................................................... 6
3.2 Valerus SmartSearch Video Search ................................................................................... 10
3.3 Business Intelligence .......................................................................................................... 12
4 Determining Camera Type ................................................................................ 14
5 Determining Camera Placement and Field of View ........................................ 16
5.1 Camera’s Viewing Angle ..................................................................................................... 16
5.2 Optimizing the Field of View ............................................................................................... 16
5.3 Determining Effective Range .............................................................................................. 17
5.3.1 References ..................................................................................................................... 21
5.3.1.1 Reference 1.1 ................................................................................................... 21
5.3.1.2 Reference 1.2 ................................................................................................... 21
5.3.1.3 Reference 2.1 ................................................................................................... 23
5.3.1.4 Reference 2.2 ................................................................................................... 24
5.3.1.5 Reference 2.3 ................................................................................................... 25
5.3.1.6 Reference 3.1 ................................................................................................... 26
5.3.1.7 Reference 3.2 ................................................................................................... 27
6 Implementing a Lighting Solution ................................................................... 28
6.1 Camera Low Light Performance ......................................................................................... 28
6.2 Determining Quality of Lighting Conditions ..................................................................... 29
6.3 Handling Poor Lighting with IR and Thermal Imaging ..................................................... 29
6.4 Lighting and Camera Placement: Additional Considerations ......................................... 30
7 Best Practices for Specific Analytics Applications........................................ 33
7.1 Perimeter Protection ............................................................................................................ 33
7.2 Business Intelligence for Retail Environments ................................................................ 35
7.2.1 People Counting ............................................................................................................. 36
7.2.2 Heat Maps and Target Path Analysis ............................................................................. 42
7.3 Traffic Management ............................................................................................................. 45
7.3.1 Main Objectives .............................................................................................................. 45
7.3.2 Relevant Analytics Rules ................................................................................................ 45
7.3.3 Camera Mounting Principles........................................................................................... 45
7.3.4 Guidelines and Tips ........................................................................................................ 46
8 Determining Analytics Capabilities to be Applied to Each Camera.............. 47
9 Defining Where/How Analytics Results will be Viewed ................................. 47
10 Determining Required Hardware & Software Specification .......................... 47
Best Practices Guide
3 August 2018
11 Determining Licensing Requirements ............................................................. 47
11.1 SQL License ......................................................................................................................... 47
11.2 Redundancy License ........................................................................................................... 47
12 Appendix A – Camera Placement Principles .................................................. 48
12.1 Basic Principles ................................................................................................................... 48
12.2 Camera Mounting Options and Impact on Field of View ................................................. 50
12.3 Camera Placement Design Tool ......................................................................................... 52
13 Appendix B – Lighting Principles .................................................................... 53
13.1 Camera Low Light Performance ......................................................................................... 53
13.2 Determining Quality of Lighting Conditions ..................................................................... 54
13.2.1 Vicon Lighting Categories .............................................................................................. 54
13.3 Handling Poor Lighting with IR and Thermal Imaging ..................................................... 58
13.4 Testing Lighting Performance ............................................................................................ 59
Best Practices Guide
4 August 2018
1 Introduction
This document describes best practices when deploying Valerus SmartAnalytics video
analytics solutions at your site. These guidelines will assist you to install and implement the
system in an optimal configuration that is customized to the specific business requirements
and physical setup of your site(s). Utilizing these best practices that are gathered by
Valerus professionals throughout the years, you will be able to maximize the value of the
solution while minimizing potential false detections and inaccurate information.
The document provides comprehensive information on various aspects and scenarios of
deployments. The appendices provide additional general information regarding cameras
and lighting.
2 Performing a Site Survey
The integrator must perform a comprehensive Site Survey of the particular site on which a
deployment of Valerus SmartAnalytics video analytics is planned, with the objective of
identifying site parameters that may affect the ability to satisfy both project requirements
and video analytics performance requirements.
The following items are documented in the Site Survey:
Requirements: Detailed video analytics requirements, to be used as acceptance
criteria for the deployed solution
Cameras: Cameras used (with their site layout) or planned to be used with video
analytics
Video Management System (VMS): Valerus
Recording, Viewing and Monitoring: physical location of the recording, viewing and
monitoring clients and servers
Forensics/Statistics: If utilized, specifying operator locations, interfaces, data
retrieval mechanism, retention time and export format
Network infrastructure
Failover requirements
Lighting conditions
Environmental factors
Best Practices Guide
5 August 2018
3 Verifying Valerus SmartAnalytics Products
Deployment Requirements
This section describes Valerus SmartAnalytics’ offering of video analytics solutions and will
help you map deployment requirements to existing product capabilities and verify if the
requirements can be implemented. Contact Vicon Technical Support if you’re uncertain
about how a specific requirement can be implemented. If you identify a requirement which
cannot be currently met, go back to the end user and help them modify the requirement so
that it can be met.
Vicon’s offering includes the following applications:
Valerus SmartActions Real-Time Detections and Alerts
Defining events and scenarios and receiving real-time alerts when such events are
detected
Valerus SmartSearch Video Search
Searching through recorded video after an incident to locate specific video footage
Valerus Business Intelligence
Analyzing motion patterns, counting and generating statistical reports
Best Practices Guide
6 August 2018
3.1 Real-time Video Analysis and Alerts
The following table describes the Valerus SmartAction real-time video analytics features
available with Valerus SmartAnalytics’ video analytics product.
Application
Main Usages
Reference image
Person
moving in an
area
Detects and generates an alert
when a person enters or moves
within a user-defined region.
Typically implemented to protect
indoor and outdoor sterile zones.
Event generation can be filtered
by direction of movement, time,
distance travelled, and speed.
Person
crossing a
line
Detects and generates an alert
when a user-defined virtual line is
crossed by a person.
Can be used in both indoor and
outdoor environments. Typically
used for perimeter protection
(including fence trespassing) or
for detecting illegal movements
(wrong way).
Also used to detect a person
entering or leaving a designated
area. Allows definition of a
particular crossing direction as a
detection criterion.
Person
tailgating
Detects and generates an alert
when two persons cross a user-
defined virtual line, in a particular
direction, within a short
timeframe. The virtual line,
direction and timeframe are user-
defined. Typically used to alert
against illegal access through an
access-controlled point.
Person
loitering
Detects and generates an alert
when a person is present in a
user-defined region for a user-
defined duration. Typically used
to detect potential security
threats.
Best Practices Guide
7 August 2018
Application
Main Usages
Reference image
People
crowding
Detects and generates an alert
when crowd gathering occurs
within a user-defined region.
Users may define detection
criteria such as: the rate of region
coverage, in percentage, and
duration.
People
Occupancy
Detects and generates an alert
when grouping (specific number
of people gathering) occurs within
a user-defined region. Users may
configure the number of people in
a group, and the duration of
gathering.
Vehicle
moving in an
area
Detects and generates an alert
when a vehicle moves in an area.
Event generation can be filtered
by direction of movement, time,
distance travelled, and speed.
Typically used for roads safety
and parking lots security
applications.
Vehicle
crossing a
line
Detects and generates an alert
when a vehicle enters or leaves
an area. Configurable criteria are:
virtual line to be crossed, distance
travelled (before and after the
virtual line is crossed), and
speed.
Best Practices Guide
8 August 2018
Application
Main Usages
Reference image
Tailgating
vehicle
Detects and generates an alert
when two vehicles cross a user-
defined virtual line, in a specific
direction, within a short
timeframe. The virtual line,
direction and timeframe are
configurable. Typically used to
detect illegal access within an
access control point, such as a
parking lot.
Stopped
vehicle
Detects and generates an alert
when a vehicle stops in an area
for a period. Area and time are
user-defined. Typically used to
detect vehicles stopping in
restricted areas, on highway
shoulders, or generally for illegal
parking.
Vehicle
Speed
Analysis
Detects a decrease in vehicles
average speed in a predefined
area for longer than a predefined
time threshold.
Suspicious
object
Detects and generates an alert
when an object is left unattended
in an area for a period. Area,
object size, and time are user-
defined.
Best Practices Guide
9 August 2018
Application
Main Usages
Reference image
Asset
protection
Detects and generates an alert
after a user-defined asset is
removed. The time that lapses for
the alert to be issued following
the asset removal is user-defined.
Lighting
Detection
Detects a light (signal)
appearance in a predefined area
of the camera field of view longer
than a predefined time threshold.
Detection of
moving
people or
vehicles on
PTZ presets
Detects and generates an alert
when a person or vehicle enters,
moves in, or exits a user-defined
area, or crosses a user-defined
virtual line, on PTZ camera
presets. The PTZ camera presets
tour, detection time on each
preset and direction/zones are
user-defined.
PTZ auto-
tracking
originated by
detection on
PTZ presets
Detects when a person enters,
moves in or exits a user-defined
area, or crosses a user-defined
virtual line, and immediately starts
to autonomously track them while
controlling the PTZ camera
movements to keep the target in
the field of view. The PTZ camera
presets tour is user-defined.
Detection time on each preset is
user-defined.
Best Practices Guide
10 August 2018
3.2 Valerus SmartSearch Video Search
This section describes the forensic and post-event analysis applications of Valerus
SmartSearch video search and analysis capabilities.
Valerus SmartSearch offers an intuitive search engine that allows you to execute search
queries based on the following parameters and criteria:
Target Type – people, vehicles, static objects
Event Type – moving, stationary, crossing a line, occupancy, crowding
Search by color and/or size
Search within defined time frames
Search on selected cameras or group of cameras
Search for Similar Targets – Once a target is observed, a search can be conducted to
locate additional appearances of the same or similar target in the recorded video.
The following table shows the available output results for these queries.
Application
Reference Image
Thumbnail based
investigation
Best Practices Guide
11 August 2018
Application
Reference Image
Video summary
Best Practices Guide
12 August 2018
3.3 Business Intelligence
This section describes the business intelligence applications of Valerus Business
Intelligence capabilities.
Application
Main Usages
Reference Image
People
counting
Counts people crossing a
virtual line in a predefined
direction.
Various types of statistical
reports can be generated in
different timeframes, such as
overall daily traffic, traffic
density hot spots, and a
comparison between specific
hours and days.
Heat maps -
occupancy and
dwell time
display as hot
zones
Enables visualization of
occupancy levels in specified
areas in the camera’s field of
view (or across a site map
associated with multiple
cameras) for easy
identification of high/low
occupancy zones.
Motion path
analysis
Produces graphical
presentation of all motion
paths in a scene (or across a
site map), for identification of
trends / anomalies. Also used
for forensic investigation.
Video playback can be
activated for each path.
Site Map
Enables ‘Heat Map’ and
‘Motion Path Analysis’
functionalities on a site map,
indicating multiple cameras
fields of view on a single map.
Statistical
analysis
Summarizes video search
results and generates
comprehensive statistical
reports, for specified group of
cameras and within a defined
time frame.
Best Practices Guide
13 August 2018
Application
Main Usages
Reference Image
Vehicle
counting
Counts vehicles crossing a
virtual line in a predefined
direction. Various types of
statistical reports can be
generated in different
timeframes, such as overall
daily traffic, weekly and
monthly comparisons, traffic
density hot spots, comparison
between specific hours and
days, etc.
Vehicle Speed
Analysis
Best Practices Guide
14 August 2018
4 Determining Camera Type
This section describes how to select cameras for a site where the cameras are not yet
installed or selected. Select from three main camera types:
Fixed CCD\CMOS
This is the most common camera type used with video analytics.
There is a long list to choose from, ranging from analog cameras to megapixel IP
cameras.
Analytics performance can be increased by deploying the capabilities of:
1. Wide Dynamic Range
2. Automatic switching between day and night
Thermal
Select a thermal camera in case of either:
Limited or no lighting is available at night -or-
You want the detection to cover large distances (over 80 meters) with a single
camera
It is not advisable to deploy thermal cameras with rules utilized to detect stationary
targets such as:
Stopped Vehicle
Suspicious Object
Asset Protection
Pan-Tilt-Zoom (PTZ)
PTZ cameras are used with analytics in the following case:
To cover a large area with a smaller number of cameras.
In this case, the PTZ is set to tour between several presets and perform event
detection at each preset. Note that only a limited set of rules apply to detection on
presets, including: ‘Person/Vehicle moving in an area’ and ‘Person/Vehicle
crossing a line’
Best Practices Guide
15 August 2018
The tables below provide additional information on camera types:
Sensor and imaging:
Type
Characteristics
Main Usage
Compatibility with
Video Analytics
Standard CCD /
CMOS
Commonly used color
camera
Any common
scenario
Very high
Thermal
Infra-Red radiation
imaging (temperature
based)
Complete darkness
Very long distances
Very high
Extreme low-light
Capable of producing a
viewable color image at
0.3 Lux or less, due to
very long iris exposure
time
Poorly lit scenes with
almost complete
darkness
Very low
Panoramic/ Fish Eye
Circular image – usually
180° / 360°
Wide panoramic
coverage of an area
with a single camera
Currently limited to
people counting,
person crossing a
line, person moving
in an area
Form factor:
Type
Characteristics
Main Usage
Compatibility with
Video Analytics
Box/Bullet
Box-shaped body
requires mounting arm or
pole
Commonly used
Indoor / Outdoor
camera
Very high
Dome
Dome shape, usually
with built-in enclosure.
Ceiling, wall and arm /
pole mounting
Commonly used
Indoor / Outdoor
camera
Very high
PTZ
Motorized Pan-Tilt-Zoom
Wide-range coverage
Operator controlled
view
Specific models for
specific applications
Best Practices Guide
16 August 2018
5 Determining Camera Placement and Field of View
Based on analytics rules requirements, selected camera types, and recommended
detection distances, you can next determine camera placement and required fields of view
for each camera. See also Appendix A – Camera Placement Principles.
5.1 Camera’s Viewing Angle
It is recommended to use cameras with viewing angles (horizontal FOV) that are narrower
than 110°.
Fisheye cameras or cameras with a horizontal field of view that is wider than 110° may
suffer from image warping that degrades analytics performance.
5.2 Optimizing the Field of View
1. To determine the ideal field of view (FOV) for video analytics per camera, the following
main criteria should be taken into consideration: Maximum target distance: The
maximum distance between the camera and the analyzed target, allowing reliable
analytics. Determined by the camera’s viewing angle and the size of targets at
maximum distance.
2. Minimum target distance: The minimum distance between the camera and the
analyzed targets, allowing reliable analytics. Determined by the camera’s viewing
angle and the size of targets at minimum distance.
3. Target separation: A camera’s field of view is considered to have good target
separation if there are minimum occlusions caused by adjacent or close-by objects,
allowing a complete view of each target separately. Good target separation is a key to
successful deployment of video analytics in scenes which are non-sterile.
4. Camera resolution: Valerus SmartAnalytics supports resolutions of 320x240
(160x120 on thermal cameras) and higher including HD and megapixel resolution,
although analytics accuracy will not be improved by resolutions higher than D1.
Each of the above criteria can be altered based on the following guidelines:
Increase Maximum Target
Distance
Decrease Minimum Target
Distance
Improve Target Separation
Increase target magnification
by using longer focal lengths
Decrease target magnification
by using shorter focal lengths
Increase the tilt angle while
striving for 90-degree angle
(camera looking straight
down)
Best Practices Guide
17 August 2018
Decrease the camera’s tilt
angle* to extend the camera’s
vertical viewing angle /
maximum viewing distance
Increase the camera’s tilt
angle* to shorten the ‘dead-
zone’
Use higher mounting heights
to achieve top-down viewing
in wider areas across the field
of view
-
Use greater mounting heights
to produce lower-sized targets
which do not suppress the
maximum allowed target size
-
* Zero degrees tilt angle refers to cameras mounted parallel to the ground.
90-degree tilt angle refers to cameras mounted orthogonally to the ground (looking
straight down)
Conclusion:
For long-range field of view, use increased focal length and low tilt angle. The
minimum viewing distance can be compensated by adding a single camera at the top
of the camera chain.
For short-range field of view, use short focal lengths, high tilt angle (as close to 90
degrees as possible), and higher mounting. The higher the camera is, the higher the
tilt angle required.
For non-sterile scenes with continuous presence of multiple people and / or vehicles,
and for crowded environments, optimize target separation by using large tilt angles
(90 degrees or as close as possible to it) and higher mounting. Height and tilt angle
compensate each other in this case.
Adequate Field of View (FOV) and Area of Interest (AOI):
Position the camera so that it mostly occupies the AOI. Exclude irrelevant areas from
the FOV such as the sky and other non-important regions. Try to keep the AOI
centered in the FOV.
Avoid concealments and truncations of detected targets as much as possible. The
view of the AOI is best without physical obstacles such as trees, buildings, poles,
signs, and any other static object that may obstruct the view of the target (person,
vehicle or static object).
Avoid vegetation, puddles, and running water in the AOI.
5.3 Determining Effective Range
The effective range for reliable analysis and detection is determined according to target
size criteria which differ from one scenario to another.
The different scenarios are detailed in the below table: Size range criteria are based
on the relative size of targets in the FOV. They are required for reliable analysis of
people, vehicles, and static objects. Size range criteria are used across typical
scenarios of camera mounting and scenes learning.
‘angled’ refers to cameras positioned with a tilt angle of 20°-50° (cameras tilted at an
angle of 0°-20° or 50°-85° present views that are not optimal for analytics and are
therefore not recommended)
‘overhead’ refers to cameras positioned with a tilt angle of 85°-90° (cameras tilted at
an angle of 50°-85° present views that are not optimal for analytics and are therefore
not recommended)
See Appendix A – Camera Placement Principles for more details regarding the Camera
Placement Design Tool.
Size range for people analysis, as a % of the FOV
Best Practices Guide
18 August 2018
Scenario
Camera
Orientation*
Minimum Size
Criteria
Maximum Size
Criteria
Example
Walking / running /
loitering / crowding
Angled
Target height is
greater than or
equal to 5% of
the total image
height
Target height is
less than 33% of
the total image
height
See Reference
1.1 below
Walking / running /
loitering / crowding
Overhead
Target width is
greater than or
equal to 5% of
the total image
width
Target width is
less than 20% of
the total image
width
See Reference
1.2 below
Best Practices Guide
19 August 2018
Size range for vehicle analysis, as a % of the FOV
Scenario
Camera
Direction*
Minimum Size
Criteria
Maximum Size
Criteria
Example
Moving target on a
single lane road / street
Angled
Vehicle is viewed
from its side
Length (end to
end) is greater
than 5% of the
image width
Length (end to
end) is less
than 20% of the
image width
See
Reference
2.1 below
Static target on a single
lane road / street
Angled
Vehicle is viewed
from its side
Length (end to
end) is greater
than 5% of the
image width
Length (end to
end) is less
than 40% of the
image width
See
Reference
2.1 below
Moving target on a
multi-lane road /
highway
Overhead/Angled
mounted on
gantry or angled
camera on high
pole (6 meters or
more)
Size is greater
than 0.25% of
the total image
size
Size is less than
4% of the total
image size
See
Reference
2.2 below
Static target on a multi-
lane road / highway
Overhead/Angled
mounted on
gantry or angled
camera on high
pole (6 meters or
more)
Size is greater
than 0.25% of
the total image
size
Size is less than
10% of the total
image size
See
Reference
2.2 below
Moving target in an
open area (parking lot,
open yard)
Viewed from
multiple
directions
including front
and back with
angled cameras
Size is greater
than 0.25% of
the total image
size
Size is less than
6% of the total
image size
See
Reference
2.3 below
Static target in an open
area (parking lot, open
yard)
Viewed from
multiple
directions
including front
and back with
angled cameras
Size is greater
than 0.25% of
the total image
size
Size is less than
10% of the total
image size
See
Reference
2.3 below
Best Practices Guide
20 August 2018
Size range for static objects analysis, as a % of the FOV
Scenario
Camera Direction*
Minimal Size
Criteria
Maximal Size
Criteria
Example
Low activity scene
Good illumination
Non-appearance of
shadows, reflections,
glare
Overhead/Angled
Target size
(visible area) is
greater than
0.25% of the
image size
Target size
(visible area) is
less than 10%
of the image
size
See
Reference
3.1 below
Any indoor/outdoor
scenario with good
illumination
Overhead/Angled
Target size
(visible area) is
greater than
1% of the
image size
Target size
(visible area) is
less than 10%
of the image
size
See
Reference
3.2 below
* While overhead camera mounting is generally advised for ideal performance in non-
sterile environments (due to the principle of target separation), it is explicitly required
for some functions and scenarios, mainly for people counting, and directional based
detection rules in high activity scenes
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Vicon Valerus SmartAnalytics User guide

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Category
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Type
User guide
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