Video based detection of fall-down and other events

• US 20030058341A1
• Filed: 07/03/2002
• Published: 03/27/2003
• Est. Priority Date: 09/27/2001
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Brodsky, Tomas, Dagtas, Serhan
• Granted Patent: US 7,110,569 B2
• Time in Patent Office: Days
• US Class Current: 348/169
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30241 Trajectory
• CPC Class Codes: G06T 7/292 Multi-camera 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 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G08B 13/19602 Image analysis to detect motion of the intruder, e.g. by frame subtraction
• 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
• CPC Class Codes: G08B 13/19641 Multiple cameras having overlapping views on a single scene
• CPC Class Codes: G08B 21/043 detecting an emergency event, e.g. a fall
• CPC Class Codes: G08B 21/0476 Cameras to detect unsafe condition, e.g. video cameras
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources
• 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

A method for detecting the occurrence of a specific event is provided. The method includes: capturing image data of a scene; detecting and tracking an object of interest in the image data; analyzing features of the object of interest; comparing the analyzed features with predetermined criteria indicative of the specific event; and determining whether the specific event has occurred based on the comparison. The method is particularly useful in the monitoring of the elderly where the specific event is selected from a list comprising a fall-down, stagger, and panic gesturing.

Claims

1. A method for detecting the occurrence of a specific event, the method comprising:

capturing image data of a scene;

detecting and tracking an object of interest in the image data;

analyzing features of the object of interest;

comparing the analyzed features with predetermined criteria indicative of the specific event; and

determining whether the specific event has occurred based on the comparison.

2. The method of claim 1, wherein the specific event is selected from a list comprising a fall-down, stagger, and panic gesturing.

3. The method of claim 1, wherein the detecting comprises segmenting the image data into at least one moving object and background objects, the at least one moving object being the object of interest.

4. The method of claim 3, wherein the object of interest is a person and the detecting further comprises:

learning and recognizing a human shape; and

detecting a feature of the moving object indicative of a person.

5. The method of claim 4, wherein the detecting of a feature of the moving object indicative of a person comprises detecting a face on the moving object.

6. The method of claim 1, wherein the analyzing comprises analyzing one or more of a temporal sequence of the object of interest, a motion characteristics of the object of interest, and a trajectory of the object of interest.

7. The method of claim 6, wherein the specific event is a fall-down and the predetermined criteria indicative of the fall-down comprises at least one of:

whether the temporal sequence indicates a transition from an upright pose to a lying pose for the object of interest;

whether the motion characteristics indicates a downward motion within a predetermined time period for the object of interest; and

whether there is an abrupt change in the trajectory for the object of interest.

8. The method of claim 6, wherein the specific event is a stagger and the predetermined criteria indicative of the stagger comprises at least one of:

whether the temporal sequence indicates a back and forth motion for the object of interest;

whether the motion characteristics indicates an irregular motion for the object of interest; and

whether there is an some abruptness in the trajectory for the object of interest without significant changes in body pose.

9. The method of claim 6, wherein the specific event is a panic gesture and the predetermined criteria indicative of the panic gesture comprises at least one of:

whether the temporal sequence indicates a periodic motion in a particular region of the object of interest; and

whether the motion characteristics indicates a fast irregular motion in the particular region of the object of interest.

10. The method of claim 1, wherein the determining step comprises assigning a factor indicative of how well each of the analyzed features comply with the predetermined criteria indicative of the specific event and applying an arithmetic expression to the factors to determine a likelihood that the specific event has occurred.

11. A computer program product embodied in a computer-readable medium for detecting the occurrence of a specific event, the computer program product comprising:

computer readable program code means for capturing image data of a scene;

computer readable program code means for detecting and tracking an object of interest in the image data;

computer readable program code means for analyzing features of the object of interest;

computer readable program code means for comparing the analyzed features with predetermined criteria indicative of the specific event; and

computer readable program code means for determining whether the specific event has occurred based on the comparison.

12. The computer program product of claim 11, wherein the detecting comprises computer readable program code means for segmenting the image data into at least one moving object and background objects, the at least one moving object being the object of interest.

13. The computer program product of claim 12, wherein the object of interest is a person and the detecting further comprises:

computer readable program code means for learning and recognizing a human shape; and

computer readable program code means for detecting a feature of the moving object indicative of a person.

14. The computer program product of claim 13, wherein the detecting of a feature of the moving object indicative of a person comprises computer readable program code means for detecting a face on the moving object.

15. The computer program product of claim 11, wherein the analyzing comprises computer readable program code means for analyzing one or more of a temporal sequence of the object of interest, a motion characteristics of the object of interest, and a trajectory of the object of interest.

16. The computer program product of claim 11, wherein the determining step comprises computer readable program code means for assigning a factor indicative of how well each of the analyzed features comply with the predetermined criteria indicative of the specific event and applying an arithmetic expression to the factors to determine a likelihood that the specific event has occurred.

17. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for detecting the occurrence of a specific event, the method comprising:

capturing image data of a scene;

detecting and tracking an object of interest in the image data;

analyzing features of the object of interest;

comparing the analyzed features with predetermined criteria indicative of the specific event; and

determining whether the specific event has occurred based on the comparison.

18. The program storage device of claim 17, wherein the detecting comprises segmenting the image data into at least one moving object and background objects, the at least one moving object being the object of interest.

19. The program storage device of claim 18, wherein the object of interest is a person and the detecting further comprises:

learning and recognizing a human shape; and

detecting a feature of the moving object indicative of a person.

20. The program storage device of claim 19, wherein the detecting of a feature of the moving object indicative of a person comprises detecting a face on the moving object.

21. The program storage device of claim 17, wherein the analyzing comprises analyzing one or more of a temporal sequence of the object of interest, a motion characteristics of the object of interest, and a trajectory of the object of interest.

22. The program storage device of claim 17, wherein the determining step comprises assigning a factor indicative of how well each of the analyzed features comply with the predetermined criteria indicative of the specific event and applying an arithmetic expression to the factors to determine a likelihood that the specific event has occurred.

23. An apparatus for detecting the occurrence of a specific event, the apparatus comprising:

at least one camera for capturing image data of a scene;

a memory for storing predetermined criteria indicative of the specific event; and

a processor for analyzing the captured image data to;

detect and track an object of interest in the image data;

analyze features of the object of interest;

compare the analyzed features with the predetermined criteria indicative of the specific event; and

determine whether the specific event has occurred based on the comparison.