Intelligent camera selection and object tracking

• US 8,174,572 B2
• Filed: 03/24/2006
• Issued: 05/08/2012
• Est. Priority Date: 03/25/2005
• Status: Active Grant

• Current Assignee: Johnson Controls Tyco IP Holdings LLP (Johnson Controls International plc)
• Original Assignee: Sensormatic Electronics LLC (Johnson Controls International plc)
• Inventors: Buehler, Christopher J., Cannon, Howard I.
• Primary Examiner(s): NGUYEN, LUONG TRUNG
• Application Number:
  US11/388,759
• Publication Number:
  US 20100002082A1
• Time in Patent Office: 2,237 Days
• Field of Search: None
• US Class Current: 348/143
• CPC Class Codes: G08B 13/19645 Multiple cameras, each having view on one of a plurality of scenes, e.g. multiple cameras for multi-room surveillance or for tracking an object by view hand-over
• CPC Class Codes: G08B 13/19693 using multiple video sources viewed on a single or compound screen

Abstract

Methods and systems for creating video from multiple sources utilize intelligence to designate the most relevant sources, facilitating their adjacent display and/or catenation of their video streams.

Claims

1. A video surveillance system comprising:

a user interface comprising;

a primary camera pane for displaying a primary video data feed captured by a primary video surveillance camera;

two or more camera panes in proximity to the primary camera pane, each proximate camera pane for displaying secondary video data feeds captured by one of a set of secondary video surveillance cameras;

a tracking module for tracking movement of an object in one of the secondary video data feeds and, based thereon, replacing the primary video data feed in the primary camera pane with the secondary video data feed having the tracked object; and

a camera selection module for selecting a new secondary video data feed for display in each of the proximate camera panes based at least in part on a likelihood-of-transition metric, wherein the likelihood-of-transition metric is determined according to steps comprising;

(i) defining a set of candidate video data feeds, and (ii) assigning, to each candidate video data feed, an adjacency probability representing a likelihood that an object tracked in the primary camera pane will transition into the candidate video data feed.

2. The system of claim 1 wherein the set of secondary video surveillance cameras is based on spatial relationships between the primary video surveillance camera and a plurality of video surveillance cameras.

3. The system of claim 1 wherein the primary video data feed displayed in the primary camera pane is divided into two or more sub-regions.

4. The system of claim 3 wherein the set of secondary video surveillance cameras is based on a selection of one of the two or more sub-regions.

5. The system of claim 3 further comprising an input device for facilitating selection of a sub-region of the primary video data feed displayed in the primary camera pane.

6. The system of claim 1 further comprising an input device for facilitating the selection of an object of interest within the primary video data feed shown in the primary camera pane.

7. The system of claim 6 wherein the set of secondary video surveillance cameras is based on the selected object of interest within the primary video data feed shown in the primary camera pane.

8. The system of claim 6 wherein the set of secondary video surveillance cameras is based on motion of the selected object of interest within the primary video data feed shown in the primary camera pane.

9. The system of claim 6 wherein the set of secondary video surveillance cameras is based on an image quality of the selected object of interest within the video data shown in the primary camera pane.

10. The system of claim 1 wherein the camera selection module further determines the placement of the two or more proximate camera panes with respect to each other.

11. The system of claim 1 further comprising an input device for selecting one of the secondary video data feeds and thereby causing the camera selection module to designate the selected secondary video data feed as the primary video data feed and determining a second set of secondary video data feeds to be displayed in the proximate camera panes.

12. A method of selecting video data feeds for display, comprising:

presenting a primary video data feed in a primary video data pane;

receiving an indication of an object in the primary video data pane;

presenting a secondary video data feed in a secondary video data pane in response to the indication;

tracking movement of the indicated object in the secondary video data feed and, based thereon, replacing the primary video data feed with the secondary video data feed in the primary video data pane; and

selecting a new secondary video data feed for display in the secondary video data pane based at least in part on a likelihood-of-transition metric, wherein the likelihood-of-transition metric is determined according to steps comprising;

(i) defining a set of candidate video data feeds, and (ii) assigning, to each candidate video data feed, an adjacency probability representing a likelihood that an object tracked in the primary video data pane will transition into the candidate video data feed.

13. The method of claim 12 wherein the adjacency probabilities vary according to predefined rules.

14. The method of claim 12 wherein the set of candidate video data feeds represent a subset of available data feeds, the set of candidate video data feeds being defined according to predefined rules.

15. The method of claim 12 wherein the adjacency probabilities are stored in a multi-dimensional matrix.

16. The method of claim 15 wherein the multi-dimensional matrix comprises a dimension based on the number of candidate video data feeds.

17. The method of claim 15 wherein the multi-dimensional matrix comprises a time-based dimension.

18. The method of claim 15 further comprising segmenting the multi-dimensional matrix into sub-matrices based, at least in part, on the adjacency probabilities.

19. The method of claim 12 wherein the adjacency probabilities are based at least in part on historical data.