Video surveillance system employing video primitives

Patent metadata

Field	Value
Publication number	US-10026285-B2
Application number	US-201615044902-A
Country	US
Kind code	B2
Filing date	Feb 16, 2016
Priority date	Oct 24, 2000
Publication date	Jul 17, 2018
Grant date	Jul 17, 2018

Abstract

A video surveillance system is set up, calibrated, tasked, and operated. The system extracts video primitives and extracts event occurrences from the video primitives using event discriminators. The system can undertake a response, such as an alarm, based on extracted event occurrences.

First claim

What is claimed is:

1. A method of video surveillance, comprising:
receiving, by a computer system, a video comprising video images from a video sensor,
the computer system performing the steps of:
analyzing the video to detect stationary objects in the video using background subtraction of a background model;
analyzing the video to detect people in the video by using frame differencing to detect foreground objects;
upon detecting a first stationary object in the video, defining a zone as a portion of the video around the first stationary object, defining the zone being responsive to a location of the first stationary object, the zone being defined to be larger than an outer boundary of the first stationary object and smaller than a field of view of the video, a size of the zone allowing detection of multiple non-overlapping objects;
tracking a duration that the first stationary object remains stationary;
determining an occurrence of an external event;
issuing an alert in response to determining that the duration of time the first stationary object has remained stationary exceeds a threshold while no person of interest detected in the video has been inside the zone and the occurrence of the external event; and
determining a crowd density in the video,
wherein the size of the zone is determined dynamically and is responsive to the determined crowd density.

2. The method of claim 1 , wherein the person of interest comprises any person detected in the video.

3. The method of claim 1 , further comprising detecting a person leaving the first stationary object as the person of interest.

4. The method of claim 1 , wherein the size of the zone is determined prior to the detecting of the first stationary object.

5. The method of claim 4 , wherein the zone is one of a circle, ellipse or a rectangle.

6. The method of claim 4 , wherein the size of the zone is selected responsive to a selection by a user.

7. The method of claim 1 , wherein the person of interest comprises a person detected as leaving the first stationary object and detected as having been in the zone longer than a first period of time.

8. The method of claim 1 , wherein the zone has a size defined in an image space that varies as a function of the location of the first stationary object.

9. The method of claim 1 , wherein the zone is defined as a shape in the real-world of the video independent of detecting the first stationary object.

10. The method of claim 1 , wherein the size of the zone is determined by performing an interpolation or an extrapolation of a first shape.

11. The method of claim 10 , wherein the first shape is input by a user.

12. The method of claim 1 , further comprising:
tracking a person responsible for leaving behind the first stationary object.

13. The method of claim 1 , further comprising permitting a user to set, via a user interface, at least one parameter selected from the group consisting of: a size of the zone, a shape of the zone, and the duration of time.

14. A method of video surveillance, comprising:
receiving, by a computer system, a video comprising video images from a video sensor,
the computer system performing the steps of:
analyzing the video to detect stationary objects in the video using background subtraction of a background model;
analyzing the video to detect people in the video by using frame differencing to detect foreground objects;
upon detecting a first stationary object in the video, defining a zone as a portion of the video around the first stationary object, defining the zone being responsive to a location of the first stationary object, the zone being defined to be larger than an outer boundary of the first stationary object and smaller than a field of view of the video, a size of the zone allowing detection of multiple non-overlapping objects;
tracking a duration that the first stationary object remains stationary;
determining an occurrence of an external event;
issuing an alert in response to the determining of the occurrence of the external event and determining that the duration of time the first stationary object has remained stationary exceeds a threshold while at least one of the following occurs:
no person of interest detected in the video has been detected as being in the zone, and
no person of interest detected in the video has been detected as being in the zone longer than a first period of time; and

determining a crowd density in the video,
wherein the size of the zone is determined dynamically and is responsive to the determined crowd density.

15. The method of claim 14 , further comprising permitting a user to set, via a user interface, at least one parameter selected from the group consisting of: a size of the zone, a shape of the zone, and the duration of time.

16. A method of video surveillance, comprising:
receiving, by a computer system, a video comprising video images from a video sensor,
the computer system performing the steps of:
analyzing the video to detect stationary objects in the video using background subtraction of a background model;
analyzing the video to detect people in the video by using frame differencing to detect foreground objects;
upon detecting a first stationary object in the video, defining a zone as a portion of the video around the first stationary object, defining the zone being responsive to a location of the first stationary object, the zone being defined to be larger than an outer boundary of the first stationary object and smaller than a field of view of the video, a size of the zone allowing detection of multiple non-overlapping objects;
tracking a duration that the first stationary object remains stationary;
determining an occurrence of an external event;
issuing an alert in response to determining that the duration of time the first stationary object has remained stationary exceeds a threshold while no person of interest detected in the video has been inside the zone and the occurrence of the external event; and
determining a security threat level,
wherein the size of the zone is responsive to the determined security threat level.

17. The method of claim 16 , further comprising permitting a user to set, via a user interface, at least one parameter selected from the group consisting of: a size of the zone, a shape of the zone, and the duration of time.

18. A method of video surveillance, comprising:
receiving, by a computer system, a video comprising video images from a video sensor,
the computer system performing the steps of:
analyzing the video to detect stationary objects in the video using background subtraction of a background model;
analyzing the video to detect people in the video by using frame differencing to detect foreground objects;
upon detecting a first stationary object in the video, defining a zone as a portion of the video around the first stationary object, defining the zone being responsive to a location of the first stationary object, the zone being defined to be larger than an outer boundary of the first stationary object and smaller than a field of view of the video, a size of the zone allowing detection of multiple non-overlapping objects;
tracking a duration that the first stationary object remains stationary;
determining an occurrence of an external event; and
issuing an alert in response to determining that the duration of time the first stationary object has remained stationary exceeds a threshold while no person of interest detected in the video has been inside the zone and the occurrence of the external event,
wh

Assignees

• Avigilon Fortress Corportion
• Avigilon Fortress Corp

Inventors

• Venetianer Peter L
• Lipton Alan J
• Hu Yongtong
• Martone Andrew J
• Yin Weihong
• Yu Li
• Zhang Zhong

Classifications

• G08B13/19615 Primary

  wherein said pattern is defined by the user · CPC title

• G08B13/19697

  Arrangements wherein non-video detectors generate an alarm themselves · CPC title

• G08B21/0476

  Cameras to detect unsafe condition, e.g. video cameras · CPC title

• G06F17/30811

  Physics · mapped topic

• G06K9/00778

  Physics · mapped topic