COMPUTING DEVICE AND HOUSEHOLD MONITORING METHOD USING THE COMPUTING DEVICE

• US 20130147917A1
• Filed: 08/01/2012
• Published: 06/13/2013
• Est. Priority Date: 12/13/2011
• Status: Abandoned Application

• Current Assignee: Hon Hai Precision Industry Co., Ltd.
• Original Assignee: Hon Hai Precision Industry Co., Ltd.
• Inventors: LEE, HOU-HSIEN, LEE, CHANG-JUNG, LO, CHIH-PING
• Application Number:
  US13/563,828
• Publication Number:
  US 20130147917A1
• Time in Patent Office: Days
• US Class Current: 348/46
• CPC Class Codes: G01S 17/06 Systems determining position data of a target
• CPC Class Codes: G01S 17/89 for mapping or imaging
• 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

Abstract

In a household monitoring method using a computing device, the computing device is connected to one or more depth-sensing cameras and an alarm device. The computing device controls the depth-sensing cameras to capture real-time images of monitored areas in front of the depth-sensing cameras. A presence of a person is detected from the images. If the person is detected to be in exigency, the computing device notifies relevant personnel of the exigency.

Claims

1. A household monitoring method being executed by a processor of a computing device, the method comprising:

controlling a plurality of depth-sensing cameras connected to the computing device to capture real-time images of monitored areas in front of the depth-sensing cameras;

detecting a presence of a person in the images;

detecting whether the person present in the images is in exigency; and

notifying relevant personnel of the exigency upon condition that the person is in exigency.

2. The method of claim 1, further comprising:

detecting a presence of a specific person in an image of a specific monitored area; and

notifying the relevant personnel of the presence of the specific person in the image of the specific monitored area.

3. The method of claim 1, wherein the person is detected by comparing each of the images with samples of human images.

4. The method of claim 1, wherein the person is detected using a template matching method or an appearance-based statistical method.

5. The method of claim 1, wherein each of the depth-sensing cameras obtains a distance between a lens of the depth-sensing camera and each point on an object to be captured, and each of the images includes distance information between lens of the depth-sensing camera and each point on the object in the image, and wherein the person is detected according to the distance information of the object in the image.

6. The method of claim 1, wherein each of the depth-sensing cameras is a time-of-flight (TOF) camera.

7. A computing device, comprising:

a storage system;

at least one processor; and

a household monitoring system comprising one or more programs that are stored in the storage system and executed by the at least one processor, the one or more programs comprising instructions to;

control a plurality of depth-sensing cameras connected to the computing device to capture real-time images of monitored areas in front of the depth-sensing cameras;

detect a presence of a person in the images;

detect whether the person present in the images is in exigency; and

notify relevant personnel of the exigency upon condition that the person is detected in exigency.

8. The computing device of claim 7, wherein the one or more programs further comprise instructions to:

detect a presence of a specific person in an image of a specific monitored area; and

notify the relevant personnel of the presence of the specific person in the image of the specific monitored area.

9. The computing device of claim 7, wherein the person is detected by comparing each of the images with samples of human images.

10. The computing device of claim 7, wherein the person is detected using a template matching method or an appearance-based statistical method.

11. The computing device of claim 7, wherein each of the depth-sensing cameras obtains a distance between a lens of the depth-sensing camera and each point on an object to be captured, and each of the images includes distance information between lens of the depth-sensing camera and each point on the object in the image, wherein the person is detected according to the distance information of the object in the image.

12. The apparatus of claim 7, wherein each of the depth-sensing cameras is a time-of-flight (TOF) camera.

13. A non-transitory computer-readable storage medium storing a set of instructions, the set of instructions capable of being executed by a processor of a computing device to implement a household monitoring method, the method comprising:

controlling a plurality of depth-sensing cameras connected to the computing device to capture real-time images of monitored areas in front of the depth-sensing cameras;

detecting a presence of a person in the images;

detecting whether the person present in the images is in exigency; and

notifying relevant personnel of the exigency upon condition that the person is detected in exigency.

14. The storage medium of claim 13, wherein the method further comprises:

detecting a presence of a specific person in an image of a specific monitored area; and

notifying the relevant personnel of the presence of the specific person in the image of the specific monitored area.

15. The storage medium of claim 13, wherein the person is detected by comparing each of the images with samples of human images.

16. The storage medium of claim 13, wherein the person is detected using a template matching method or an appearance-based statistical method.

17. The storage medium of claim 13, wherein each of the depth-sensing cameras obtains a distance between a lens of the depth-sensing camera and each point on an object to be captured, each of the images includes distance information between lens of the depth-sensing camera and each point on the object in the image, wherein the person is detected according to the distance information of the object in the image.

18. The storage medium of claim 13, wherein each of the depth-sensing cameras is a time-of-flight (TOF) camera.