Interior location identification

• US 8,891,816 B2
• Filed: 05/03/2013
• Issued: 11/18/2014
• Est. Priority Date: 05/13/2011
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Billingham, James, Bowyer, Helen, Brown, Kevin, Jellard, Edward, White, Graham
• Primary Examiner(s): Rush, Eric
• Application Number:
  US13/887,088
• Publication Number:
  US 20130243326A1
• Time in Patent Office: 564 Days
• Field of Search: 382/100, 382/103, 382/104, 382/153, 382/154, 382/181, 382/187, 382/209, 382/217, 382/218, 382/321, 382/325, 348/113, 348/116, 701/1, 701/2, 701/27, 701/28, 701/400, 701/408, 701/409, 701/450, 701/461, 701519-524, 701/526
• US Class Current: 382/100
• CPC Class Codes: G06V 20/30 in albums, collections or shared content, e.g. social network photos or video

Abstract

A parse module calibrates an interior space by parsing objects and words out of an image of the scene and comparing each parsed object with a plurality of stored objects. The parse module further selects a parsed object that is differentiated from the stored objects as the first object and stores the first object with a location description. A search module can detect the same objects from the scene and use them to determine the location of the scene.

Claims

1. A method for interior location identification comprising:

parsing, by use of a processor, at least one object from a first image of an interior space;

comparing each parsed object with a plurality of stored objects;

selecting a parsed object that is differentiated from the stored objects based on a similarity score as a first object, wherein common objects, identified by having a high similarity score, and parsed stationary objects that are identified as potentially mobile are excluded from selection; and

indexing a location description of the interior space with the first object in a location record.

2. The method of claim 1, further comprising:

scanning the first image; and

appending a secondary location indication to the location record.

3. The method of claim 2, wherein the secondary location indication is selected from the group consisting of a wireless network identification and a cellular telephone network identification.

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

identifying the first object from a second image of the interior space; and

retrieving the location description in response to identifying the first object.

5. The method of claim 4, the method further comprising:

scanning the second image; and

narrowing a scope for identifying the first object using a secondary location indication.

6. The method of claim 1, wherein the first object is text and an Optical Character Recognition (OCR) process parses the text.

7. The method of claim 1, wherein the location description comprises at least one of a room number, an address, a navigation direction, a building map, and coordinates.

8. A method for deploying a computer program product, comprising integrating computer readable program code into a computing system, wherein the computer readable program code in combination with the computing system performs the following:

parsing at least one object from a first image of an interior space;

comparing each parsed object with a plurality of stored objects;

selecting a parsed object that is differentiated from the stored objects based on a similarity score as a first object, wherein common objects, identified by having a high similarity score, and parsed stationary objects that are identified as potentially mobile are excluded from selection; and

indexing a location description of the interior space with the first object in a location record.

9. The method of claim 8, further comprising:

scanning the first image; and

appending a secondary location indication to the location record.

10. The method of claim 9, wherein the secondary location indication is selected from the group consisting of a wireless network identification and a cellular telephone network identification.

11. The method of claim 8, the method further comprising:

identifying the first object from a second image of the interior space; and

retrieving the location description in response to identifying the first object.

12. The method of claim 11, the method further comprising:

scanning the second image; and

narrowing a scope for identifying the first object using a secondary location indication.

13. The method of claim 8, wherein the first object is text and an Optical Character Recognition (OCR) process parses the text.

14. The method of claim 8, wherein the location description comprises at least one of a room number, an address, a navigation direction, a building map, and coordinates.