Directional object detection

• US 9,721,168 B2
• Filed: 08/18/2016
• Issued: 08/01/2017
• Est. Priority Date: 11/15/2012
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: Avigilon Analytics Corporation
• Inventors: Saptharishi, Mahesh, Marman, Douglas H.
• Primary Examiner(s): Natnael, Paulos M
• Assistant Examiner(s): Rahman, Mustafizur
• Application Number:
  US15/240,933
• Publication Number:
  US 20170185847A1
• Time in Patent Office: 348 Days
• Field of Search: 348135, 348143, 348142, 348149, 348153, 348154, 348156, 348158, 348169, 3482221, 348565, 382103, 382107, 382154, 382166, 382282, 715700, 715764, 345419, 345652
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30241 Trajectory
• CPC Class Codes: G06T 2207/30242 Counting objects in image
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/215 Motion-based segmentation
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 20/44 Event detection
• CPC Class Codes: G06V 20/49 Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: G08B 13/19613 Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
• CPC Class Codes: G08B 13/2491 Intrusion detection systems, i.e. where the body of an intruder causes the interference with the electromagnetic field
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources
• CPC Class Codes: H04N 7/183 : for receiving images from a single remote source
• CPC Class Codes: H04N 7/188 : Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position signal generation from motion picture films H04N5/253

Abstract

Video analytics is used to track an object of interest represented in video data representing the field of view of a scene observed by a video camera. A multidimensional virtual beam is used to detect whether the tracked object of interest is continually present in a detection zone within the field view of the scene. An occurrence of an event is signaled when the tracked object of interest is continually present in the detection zone during a period beginning when the tracked object of interest enters the detection zone and ending when the tracked object of interest leaves the detection zone through the opposite side, after having completely crossed through the detection zone. Use of a virtual beam detection zone reduces false alarms as compared to the numbers of incidences of false alarms of traditional detection methods, while adding several features and benefits.

Claims

1. A system comprising:

at least one video camera configured to monitor whether one or more people are passing through a detection zone within a field of view of a scene;

memory;

a processor; and

a housing containing the at least one video camera, the memory and the processor, and

the memory storing instructions that, when executed by the processor, cause the processor to;

receive video data representing the field of view of the scene observed by the at least one video camera, the video data including a plurality of video frames captured by the at least one video camera during a time period;

use video analytics to track the people represented in the video data;

configure the detection zone, the detection zone including an entrance side and an exit side positioned opposite to each other and thereby defining opposite sides of the detection zone; and

increment a count of the people upon occurrence of an event, the event being when a tracked person, among the people, is present in the detection zone in respect of at least most of the video frames during the time period, the time period beginning when the tracked person enters the detection zone on the entrance side and ending when the tracked person leaves the detection zone from the exit side; and

use the count to monitor traffic flow patterns.

2. The system of claim 1 wherein the traffic flow patterns are traffic flow patterns in a store.

3. The system of claim 1 wherein at least one of the entrance side and the exit side comprises at least one of an arc, a circle, a dome, a sphere, a straight line, a pyramid, a box and a hexagon.

4. The system of claim 1 wherein, in configuring the detection zone, a distance between the entrance side and the exit side is determined.

5. The system of claim 4 wherein the distance between the entrance side and the exit side is lengthened to reduce a likelihood of occurrence of false alarms.

6. The system of claim 4 wherein the distance between the entrance side and the exit side is shortened to increase a sensitivity of detection.

7. A system comprising:

at least one video camera configured to monitor whether one or more vehicles are passing through a detection zone within a field of view of a scene;

memory;

a processor; and

a housing containing the at least one video camera, the memory and the processor, and

the memory storing instructions that, when executed by the processor, cause the processor to;

receive video data representing the field of view of the scene observed by the at least one video camera, the video data including a plurality of video frames captured by the at least one video camera during a time period;

use video analytics to track the vehicles represented in the video data;

configure the detection zone, the detection zone including an entrance side and an exit side positioned opposite to each other and thereby defining opposite sides of the detection zone; and

increment a count of the vehicles upon occurrence of an event, the event being when a tracked vehicle, among the vehicles, is present in the detection zone in respect of at least most of the video frames during the time period, the time period beginning when the tracked vehicle enters the detection zone on the entrance side and ending when the tracked vehicle leaves the detection zone from the exit side; and

use the count to monitor traffic flow patterns.

8. The system of claim 7 wherein at least one of the entrance side and the exit side comprises at least one of an arc, a circle, a dome, a sphere, a straight line, a pyramid, a box and a hexagon.

9. The system of claim 7 wherein, in configuring the detection zone, a distance between the entrance side and the exit side is determined.

10. The system of claim 9 wherein the distance between the entrance side and the exit side is lengthened to reduce a likelihood of occurrence of false alarms.

11. The system of claim 9 wherein the distance between the entrance side and the exit side is shortened to increase a sensitivity of detection.

12. A system comprising:

at least one video camera configured to monitor whether one or more people are passing through a detection zone within a field of view of a scene; and

a plurality of computer system modules including a video analytics module and a virtual beam module, at least one of the video analytics module and the virtual beam module being located remote from the at least one video camera; and

the computer system modules configured to;

receive video data representing the field of view of the scene observed by the at least one video camera, the video data including a plurality of video frames captured by the at least one video camera during a time period;

use video analytics to track the people represented in the video data;

configure the detection zone, the detection zone including an entrance side and an exit side positioned opposite to each other and thereby defining opposite sides of the detection zone; and

increment a count of the people upon occurrence of an event, the event being when a tracked person, among the people, is present in the detection zone in respect of at least most of the video frames during the time period, the time period beginning when the tracked person enters the detection zone on the entrance side and ending when the tracked person leaves the detection zone from the exit side; and

use the count to monitor traffic flow patterns.

13. The system of claim 12 wherein the traffic flow patterns are traffic flow patterns in a store.

14. The system of claim 12 wherein at least one of the entrance side and the exit side comprises at least one of an arc, a circle, a dome, a sphere, a straight line, a pyramid, a box and a hexagon.

15. The system of claim 12 wherein, in configuring the detection zone, a distance between the entrance side and the exit side is determined.

16. The system of claim 15 wherein the distance between the entrance side and the exit side is lengthened to reduce a likelihood of occurrence of false alarms.

17. The system of claim 15 wherein the distance between the entrance side and the exit side is shortened to increase a sensitivity of detection.

18. A system comprising:

at least one video camera configured to monitor whether one or more vehicles are passing through a detection zone within a field of view of a scene; and

a plurality of computer system modules including a video analytics module and a virtual beam module, at least one of the video analytics module and the virtual beam module being located remote from the at least one video camera; and

the computer system modules configured to;

receive video data representing the field of view of the scene observed by the at least one video camera, the video data including a plurality of video frames captured by the at least one video camera during a time period;

use video analytics to track the vehicles represented in the video data;

configure the detection zone, the detection zone including an entrance side and an exit side positioned opposite to each other and thereby defining opposite sides of the detection zone; and

increment a count of the vehicles upon occurrence of an event, the event being when a tracked vehicle, among the vehicles, is present in the detection zone in respect of at least most of the video frames during the time period, the time period beginning when the tracked vehicle enters the detection zone on the entrance side and ending when the tracked vehicle leaves the detection zone from the exit side; and

use the count to monitor traffic flow patterns.

19. The system of claim 18 wherein at least one of the entrance side and the exit side comprises at least one of an arc, a circle, a dome, a sphere, a straight line, a pyramid, a box and a hexagon.