LONG-TERM STATIC OBJECT DETECTION

• US 20160063344A1
• Filed: 08/19/2015
• Published: 03/03/2016
• Est. Priority Date: 08/27/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Fan, Quanfu, Lu, Zuoxuan, Pankanti, Sharathchandra U.
• Granted Patent: US 9,754,178 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06V 10/44 Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• 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 2201/08 Detecting or categorising vehicles

Abstract

Software for static object detection that performs the following operations: (i) detecting an object that is present in at least one image of a set of images, wherein the set of images correspond to a time period; (ii) identifying a set of corner points for the detected object; (iii) tracking the object'"'"'s presence in the set of images over the time period, wherein the object'"'"'s presence is determined by matching the set of images to a template generated based on the identified corner points; and (iv) identifying the object as a static object when an amount of time corresponding to the object'"'"'s presence in the set of images is greater than a predefined threshold.

Claims

1. A method for static object detection, the method comprising:

detecting an object that is present in at least one image of a set of images, wherein the set of images correspond to a time period;

identifying a set of corner points for the detected object;

tracking the object'"'"'s presence in the set of images over the time period, wherein the object'"'"'s presence is determined by matching the set of images to a template generated based on the identified corner points; and

identifying the object as a static object when an amount of time corresponding to the object'"'"'s presence in the set of images is greater than a predefined threshold;

wherein at least the tracking is performed by computer software running on computer hardware.

2. The method of claim 1, wherein the set of images includes frames from a video.

3. The method of claim 1, further comprising generating an alert indicating that the static object has been detected.

4. The method of claim 1, further comprising:

identifying additional corner points for the detected object during the tracking; and

updating the template based, at least in part, on the identified additional corner points.

5. The method of claim 1, further comprising utilizing a tree-based representation to manage detection of the object when the object is occluded.

6. The method of claim 1, further comprising using background information when matching the generated template to the set of images to account for lighting changes over time.

7. The method of claim 1, further comprising:

determining an amount of stability for corner points in the set of corner points;

assigning a weight to one or more of the corner points based on their respective amounts of stability; and

utilizing the weight of the one or more corner points when matching the generated template to the set of images.

8. A computer program product for static object detection, the computer program product comprising a computer readable storage medium having stored thereon:

first instructions executable by a device to cause the device to detect an object that is present in at least one image of a set of images, wherein the set of images correspond to a time period;

second instructions executable by the device to cause the device to identify a set of corner points for the detected object;

third instructions executable by the device to cause the device to track the object'"'"'s presence in the set of images over the time period, wherein the object'"'"'s presence is determined by matching the set of images to a template generated based on the identified corner points; and

fourth instructions executable by the device to cause the device to identify the object as a static object when an amount of time corresponding to the object'"'"'s presence in the set of images is greater than a predefined threshold.

9. The computer program product of claim 8, wherein the set of images includes frames from a video.

10. The computer program product of claim 8, further comprising fifth instructions executable by the device to cause the device to generate an alert indicating that the static object has been detected.

11. The computer program product of claim 8, further comprising:

fifth instructions executable by the device to cause the device to identify additional corner points for the detected object during the tracking; and

sixth instructions executable by the device to cause the device to update the template based, at least in part, on the identified additional corner points.

12. The computer program product of claim 8, further comprising fifth instructions executable by the device to cause the device to utilize a tree-based representation to manage detection of the object when the object is occluded.

13. The computer program product of claim 8, further comprising fifth instructions executable by the device to cause the device to use background information when matching the generated template to the set of images to account for lighting changes over time.

14. The computer program product of claim 8, further comprising:

fifth instructions executable by the device to cause the device to determine an amount of stability for corner points in the set of corner points;

sixth instructions executable by the device to cause the device to assign a weight to one or more of the corner points based on their respective amounts of stability; and

seventh instructions executable by the device to cause the device to utilize the weight of the one or more corner points when matching the generated template to the set of images.

15. A computer system for static object detection, the computer system comprising:

a processor(s) set; and

a computer readable storage medium;

wherein;

the processor set is structured, located, connected and/or programmed to execute instructions stored on the computer readable storage medium; and

the instructions include;

first instructions executable by the processor set to cause the system to detect an object that is present in at least one image of a set of images, wherein the set of images correspond to a time period;

second instructions executable by the processor set to cause the system to identify a set of corner points for the detected object;

third instructions executable by the processor set to cause the system to track the object'"'"'s presence in the set of images over the time period, wherein the object'"'"'s presence is determined by matching the set of images to a template generated based on the identified corner points; and

fourth instructions executable by the processor set to cause the system to identify the object as a static object when an amount of time corresponding to the object'"'"'s presence in the set of images is greater than a predefined threshold.

16. The computer system of claim 15, wherein the set of images includes frames from a video.

17. The computer system of claim 15, further comprising fifth instructions executable by the processor set to cause the system to generate an alert indicating that the static object has been detected.

18. The computer system of claim 15, further comprising:

fifth instructions executable by the processor set to cause the system to identify additional corner points for the detected object during the tracking; and

sixth instructions executable by the processor set to cause the system to update the template based, at least in part, on the identified additional corner points.

19. The computer system of claim 15, further comprising fifth instructions executable by the processor set to cause the system to utilize a tree-based representation to manage detection of the object when the object is occluded.

20. The computer system of claim 15, further comprising fifth instructions executable by the processor set to cause the system to use background information when matching the generated template to the set of images to account for lighting changes over time.