METHOD AND SYSTEM FOR TRACKING AN OBJECT-OF-INTEREST WITHOUT ANY REQUIRED TRACKING TAG THERON

• US 20190333233A1
• Filed: 02/01/2019
• Published: 10/31/2019
• Est. Priority Date: 04/25/2018
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: Avigilon Corporation (Motorola Solutions, Inc.)
• Inventors: Hu, Yanyan, Russo, Pietro, Saptharishi, Mahesh
• Granted Patent: US 11,321,592 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 2576/00 Medical imaging apparatus involving image processing or analysis A61B1/00009, A61B6/52 and A61B8/52 take precedence; image processing per se G06T; details of algorithms for analysing medical images G06T7/0012
• CPC Class Codes: A61B 5/0077 Devices for viewing the surface of the body, e.g. camera, magnifying lens
• CPC Class Codes: A61B 5/015 By temperature mapping of body part
• CPC Class Codes: A61B 5/0507 using microwaves or terahertz waves
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1113 Local tracking of patients, e.g. in a hospital or private home
• CPC Class Codes: A61B 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: G01S 13/04 Systems determining presence of a target based on relative movement of target G01S13/56
• CPC Class Codes: G01S 13/726 Multiple target tracking
• CPC Class Codes: G01S 13/862 Combination of radar systems with sonar systems
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/88 Radar or analogous systems specially adapted for specific applications electromagnetic prospecting or detecting of objects, e.g. near-field detection, G01V3/00
• CPC Class Codes: G01S 13/886 for alarm systems alarms with electrical actuation G08B13/22
• CPC Class Codes: G01S 15/86 Combinations of sonar systems with lidar systems; Combinations of sonar systems with systems not using wave reflection
• CPC Class Codes: G01S 7/417 involving the use of neural networks
• CPC Class Codes: G06F 18/251 of input or preprocessed data
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 2207/10044 Radar image
• CPC Class Codes: G06T 2207/10048 : Infrared image
• CPC Class Codes: G06T 2207/20084 : Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/20212 : Image combination
• CPC Class Codes: G06T 2207/30196 : Human being; Person
• CPC Class Codes: G06T 2207/30232 : Surveillance
• CPC Class Codes: G06T 2207/30242 : Counting objects in image
• 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 7/292 : Multi-camera tracking
• CPC Class Codes: G06T 7/593 : from stereo images
• CPC Class Codes: G06T 7/70 : Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 10/255 : Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 10/62 : relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking
• 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 2201/10 : Recognition assisted with metadata
• CPC Class Codes: G08B 21/182 : Level alarms, e.g. alarms responsive to variables exceeding a threshold
• CPC Class Codes: H04N 13/204 : using stereoscopic image cameras stereoscopic photography G03B35/00
• CPC Class Codes: H04N 13/271 : wherein the generated image signals comprise depth maps or disparity maps
• CPC Class Codes: H04N 23/54 : Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils

Abstract

Methods, systems, and techniques for tagless tracking of an object-of-interest are disclosed. Image and non-image data are generated across a plurality of camera-specific regions, and the object-of-interest is tracked over a global map formed as a composite of these regions.

Claims

1. A method for tracking an object-of-interest over a global map formed as a composite of a plurality of camera-specific regions including a first region and a second region, the method comprising:

generating, within a first three-dimensional camera, first image data depicting the object-of-interest within the first region and first non-image data representing the object-of-interest within the first region;

determining that the object-of-interest depicted in the first image data is corresponding to a same instance of the object-of-interest represented in the first non-image data by correlating the first image and first non-image data;

deriving first region coordinates of the instance of the object-of-interest from at least one of the first image and first non-image data;

employing a location of the first region and the first region coordinates to calculate first global coordinates of the instance of the object-of-interest;

generating, within a second three-dimensional camera, second image data depicting the object-of-interest within the second region and second non-image data representing the object-of-interest within the second region;

determining that the object-of-interest depicted in the second image data is corresponding to a same second instance of the object-of-interest represented in the second non-image data by correlating the second image and second non-image data;

deriving second region coordinates of the second instance of the object-of-interest from at least one of the second image and second non-image data; and

employing a location of the second region and the second region coordinates to calculate second global coordinates of the second instance of the object-of-interest, and

wherein the object-of-interest is tracked over the global map as having moved from one of the first and second global coordinates to the other of the first and second global coordinates.

2. The method as claimed in claim 1 wherein at least one of the first three-dimensional camera and the second three-dimensional camera is mounted top down.

3. The method as claimed in claim 1 wherein the first three-dimensional camera and the second three-dimensional camera are mounted top down.

4. The method as claimed in claim 1 further comprising displaying the global map within a user interface within which an indicator of the object-of-interest is superimposed on the global map.

5. The method as claimed in claim 1 further comprising creating at least one access control rule following the first global coordinates or the second global coordinates being calculated.

6. A system for tracking an object-of-interest over a global map formed as a composite of a plurality of camera-specific regions including a first region and a second region, the system comprising:

a first three-dimensional camera configured to generate;

i) first image data depicting the object-of-interest within the first region; and

ii) first non-image data representing the object-of-interest within the first region;

a second three-dimensional camera configured to generate;

i) second image data depicting the object-of-interest within the second region; and

ii) second non-image data representing the object-of-interest within the second region;

at least one tangible, non-transitory, computer-readable storage medium; and

at least one processor configured to;

determine that the object-of-interest depicted in the first image data is corresponding to a same instance of the object-of-interest represented in the first non-image data by correlating the first image and first non-image data;

derive first region coordinates of the instance of the object-of-interest from at least one of the first image and first non-image data;

calculate first global coordinates of the instance of the object-of-interest based on a location of the first region and the first region coordinates;

determine that the object-of-interest depicted in the second image data is corresponding to a same second instance of the object-of-interest represented in the second non-image data by correlating the second image and second non-image data;

derive second region coordinates of the second instance of the object-of-interest from at least one of the second image and second non-image data;

calculate second global coordinates of the second instance of the object-of-interest based on a location of the second region and the second region coordinates; and

initiate a storing of tracking data into the computer readable medium, the tracking data indicating that the object-of-interest has moved from one of the first and second global coordinates to the other of the first and second global coordinates.

7. The system as claimed in claim 6 wherein at least one of the first three-dimensional camera and the second three-dimensional camera is attached to a ceiling structure and mounted top down.

8. The system as claimed in claim 6 wherein the first three-dimensional camera and the second three-dimensional camera are attached to a ceiling structure and mounted top down.

9. The system as claimed in claim 6 wherein the at least one processor is further configured to create at least one access control rule following the first global coordinates or the second global coordinates being calculated.

10. A method for tracking an object-of-interest over a global map formed as a composite of a plurality of camera-specific regions including a first region and a second region, the method comprising:

deriving first region coordinates of an instance of the object-of-interest from a combination of first image data and first non-image data, both generated within a first three-dimensional camera and both corresponding to the instance of the object-of-interest in the first region;

employing a location of the first region and the first region coordinates to calculate first global coordinates of the instance of the object-of-interest;

deriving second region coordinates of another instance of the object-of-interest from a combination of second image data and second non-image data, both generated within a second three-dimensional camera and both corresponding to the another instance of the object-of-interest in the second region; and

employing a location of the second region and the second region coordinates to calculate second global coordinates of the another instance of the object-of-interest, and

wherein the object-of-interest is tracked over the global map as having moved from one of the first and second global coordinates to the other of the first and second global coordinates.

11. The method as claimed in claim 10 further comprising displaying the global map within a user interface within which an indicator of the object-of-interest is superimposed on the global map.

12. The method as claimed in claim 10 further comprising creating at least one access control rule following the first global coordinates or the second global coordinates being calculated.