VIDEO IDENTIFICATION AND ANALYTICAL RECOGNITION SYSTEM

• US 20140313330A1
• Filed: 04/18/2014
• Published: 10/23/2014
• Est. Priority Date: 04/19/2013
• Status: Active Grant

• Current Assignee: James Carey
• Original Assignee: James Carey
• Inventors: Carey, James
• Granted Patent: US 11,100,334 B2
• Time in Patent Office: Days
• US Class Current: 348/143
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30232 Surveillance
• 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: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/53 Recognition of crowd images, e.g. recognition of crowd congestion
• CPC Class Codes: G08B 13/19608 Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position
• CPC Class Codes: G08B 13/19613 Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion

Abstract

An analytical recognition system includes one or more video cameras configured to capture video and a video analytics module configured to perform real-time video processing and analyzation of the captured video and generate non-video data. The video analytic module includes one or more algorithms configured to identify an abnormal situation. Each abnormal situation alerts the video analytics module to automatically issue an alert and track one or more objects or individuals by utilizing the one or more video cameras. The abnormal situation is selected from the group consisting of action of a particular individual, non-action of a particular individual, a temporal event, and an externally generated event.

Claims

1. An analytical recognition system, comprising:

at least one video camera configured to capture video; and

a video analytics module configured to perform real-time video processing and analyzation of the captured video and generate non-video data, the video analytic module including one or more algorithms configured to identify an abnormal situation, each abnormal situation alerting the video analytics module to automatically issue an alert and track one or more objects or individuals by utilizing the at least one camera,

wherein the abnormal situation is selected from the group consisting of action of a particular individual, non-action of a particular individual, a temporal event, and an externally generated event.

2. An analytical system according to claim 1 wherein the video analytics module identifies and stores in a database one or more characteristics of the particular individual for future recognition by the video analytics module and the one or more algorithms to identify an abnormal situation.

3. An analytical system according to claim 2 wherein the one or more characteristics of the particular individual is selected from the group consisting of hair style, tattoos, piercings, clothing, logos, contrasting colors, gang-related indicia, and jewelry.

4. An analytical system according to claim 1 wherein the video analytics module stores the captured video in a database accessible by a user and wherein the user identifies one or more characteristics of the particular individual for future recognition by the video analytics module and the one or more algorithms to identify an abnormal situation.

5. An analytical system according to claim 4 wherein the one or more characteristics of the particular individual is selected from the group consisting of hair style, tattoos, piercings, clothing, logos, contrasting colors, gang-related indicia, and jewelry.

6. An analytical system according to claim 1 wherein the video analytics module connects to an array of cameras organized in a network and wherein upon issuance of an alert each camera in the network is utilized to track one or more objects or individuals.

7. An analytical system according to claim 1 wherein the video analytics module identifies and stores in a database one or more characteristics of the particular individual for future recognition by the video analytics module and the one or more algorithms to identify an abnormal situation and issue an alert wherein the video analytics module connects to an array of cameras organized in a network to analyze captured video.

8. An analytical system according to claim 7 wherein the one or more characteristics of the particular individual is selected from the group consisting of hair style, tattoos, piercings, clothing, logos, contrasting colors, gang-related indicia, and jewelry.

9. An analytical system according to claim 7 wherein an owner of one of the cameras in the array of cameras forming the network may opt on a subscription basis for receiving particular alerts or being part of the camera network.

10. An analytical system according to claim 2 wherein the one or more characteristics of the particular individual includes a person'"'"'s gait.

11. An analytical system according to claim 10 wherein each person'"'"'s gait is determined based on a combination of one or more of the following walking variables including:

limp, shuffle, head angle, stride, hand/arm sway, hand gestures, walk velocity, step frequency, angle between feet, and hand/arm position.

12. An analytical recognition system, comprising:

at least one video camera configured to capture a video sequence of a physical space; and

a video analytics module configured to perform real-time video processing and analyzation to determine a crowd parameter by automated processing of the video sequence of the physical space, the video analytic module including at least one algorithm configured to determine a rate of change in the crowd parameter.

13. An analytical system according to claim 12 wherein the crowd parameter is a real-time crowd count.

14. An analytical system according to claim 12 wherein the crowd parameter is a real-time crowd density estimation.

15. An analytical system according to claim 12 wherein when the rate of change in the crowd parameter exceeds a predetermined threshold, the video analytics module automatically issues an alert.

16. An analytical system according to claim 12 wherein the rate of change in the crowd parameter is indicative of crowd convergence.

17. An analytical system according to claim 16 wherein when the rate of change in the crowd parameter is indicative of crowd convergence, the video analytics module alerts security of a potential flash mob or gang robbery.

18. An analytical system according to claim 17 wherein the video analytics module is connected to an array of cameras organized in a network and wherein upon issuance of an alert each camera in the network is utilized to track one or more objects or individuals.

19. An analytical system according to claim 12 wherein the rate of change in the crowd parameter is indicative of crowd divergence.

20. An analytical system according to claim 19 wherein when the rate of change in the crowd parameter is indicative of crowd divergence, the video analytics module alerts security of a potentially hazardous situation or criminal activity.