Monitor system

• US 9,905,009 B2
• Filed: 01/29/2013
• Issued: 02/27/2018
• Est. Priority Date: 01/29/2013
• Status: Active Grant

• Current Assignee: Ramrock Video Technology Laboratory Co., Ltd., Syusei Co., Ltd.
• Original Assignee: Ramrock Video Technology Laboratory Co., Ltd., Syusei Co., Ltd.
• Inventors: Akama, Toshikazu
• Primary Examiner(s): Vaughn, Jr., William C
• Assistant Examiner(s): Noh, Jae N
• Application Number:
  US14/762,830
• Publication Number:
  US 20150324990A1
• Time in Patent Office: 1,855 Days
• Field of Search: 348143
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• 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 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G08B 13/19652 Systems using zones in a single scene defined for different treatment, e.g. outer zone gives pre-alarm, inner zone gives alarm
• CPC Class Codes: H04N 23/80 Camera processing pipelines; Components thereof

Abstract

A surveillance system 1, which is an example of a surveillance system to which the present invention is applied, includes a surveillance region storage means 2 and an image analyzing means 3. Also, the surveillance system 1 includes an effective area information storage means 4 and an object criterion information storage means 5. A detection subject can be detected efficiently by setting a first step criterion of whether or not a portion of an object in an image is included in a range of a surveillance region and a predetermined second step criterion and determining whether or not these criteria are met.

Claims

1. A method for a computing apparatus of surveilling an image pickup region of an image pickup apparatus, comprising the steps of:

storing, in a storage memory, a surveillance region that is a predetermined partial region within the image pickup region and an effective region that is another predetermined partial region that is fixed within the image pickup region at least partially overlapping with the surveillance region the effective region comprising a portion outside of the surveillance region;

receiving, at the computing apparatus, an input image from the image pickup apparatus and monitoring the surveillance region of the input image to determine whether or not at least a portion of an object in the input image is located within the surveillance region based, at least in part, on a size and a location of the object in the input image;

determining, when at least a portion of the object is determined to be located within the surveillance region based on the monitoring, whether or not the object is contained within the effective region based, at least in part, on the size and the location of the object in the input image; and

generating, by the computing apparatus, a surveillance event indication when the object is determined to be contained within the effective region based on the determining.

2. The method of claim 1, wherein the input image is a moving image.

3. The method of claim 1, wherein the effective region has a region that is not overlapped with the surveillance region.

4. The method of claim 1, further comprising the steps of:

storing at least one of either upper limit or lower limit information of a shape of the object as object criterion information; and

determining whether or not the shape of the object corresponds to being not less than the upper limit or not more than the lower limit of the stored object criterion information, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the shape determining.

5. The method of claim 1, further comprising the steps of:

storing information on a time during which the object is located within the image pickup region as image pickup region location time information;

determining whether or not the stored image pickup region location time information exceeds a predetermined time, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the time determining.

6. The method of claim 1, further comprising the steps of:

storing information on an acceleration of the object when it moves inside the image pickup region as acceleration information;

determining whether or not the stored acceleration information exceeds a predetermined acceleration, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the acceleration determining.

7. The method of claim 1, further comprising the steps of:

storing information on a color tone of the object as color tone information;

determining whether or not the stored color tone information corresponds to a predetermined color tone, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the color tone determining.

8. The method of claim 1, further comprising the steps of:

storing information on a luminance of the object as luminance information;

determining whether or not the stored luminance information corresponds to a predetermined luminance, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the luminance determining.

9. The method of claim 1, further comprising the steps of:

storing information on an area occupancy of the object within the image pickup region as area occupancy information;

determining whether or not the stored area occupancy information exceeds a predetermined area occupancy, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the occupancy determining.

10. The method of claim 1, further comprising the steps of:

storing information on a volume of sound emitted by the object as sound volume information;

determining whether or not the stored sound volume information exceeds a predetermined sound volume, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the sound volume determining.

11. The method of claim 1, further comprising the steps of:

storing information on a temperature of the object as temperature information;

determining whether or not the stored temperature information exceeds a predetermined temperature, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the temperature determining.

12. The method of claim 1, further comprising the steps of:

storing information on a humidity of the object as humidity information;

determining whether or not the stored humidity information exceeds a predetermined humidity, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the humidity determining.

13. The method of claim 1, further comprising the steps of:

storing information on an odor of the object as odor information;

determining whether or not the stored odor information corresponds to a predetermined odor or whether or not the odor information exceeds a predetermined odor intensity, wherein

the surveillance event indication generating is further conditioned upon one of a positive result and a negative result of the odor determining.

14. The method of claim 1, further comprising the step of:

notifying the surveillance event indication to a surveilling person.