SYSTEM AND METHOD FOR IDENTIFYING OBJECTS IN AN IMAGE USING POSITIONAL INFORMATION

• US 20100195872A1
• Filed: 09/18/2008
• Published: 08/05/2010
• Est. Priority Date: 09/19/2007
• Status: Abandoned Application

• Current Assignee: Panasonic Corporation (Panasonic Holdings Corporation)
• Original Assignee: Panasonic Corporation (Panasonic Holdings Corporation)
• Inventors: Velardo, Carmelo, Rigazio, Luca, Kryze, David, Morin, Philippe, Veprek, Peter
• Application Number:
  US12/678,262
• Publication Number:
  US 20100195872A1
• Time in Patent Office: Days
• US Class Current: 382/106
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69

Abstract

A computer-implemented method is provided for identifying objects in an image. The method includes: capturing a series of images of a scene using a camera; receiving a topographical map for the scene that defines distances between objects in the scene; determining distances between objects in the scene from a given image; approximating identities of objects in the given image by comparing the distances between objects as determined from the given image in relation to the distances between objects from the map. The identities of objects can be re-estimated using features of the objects extracted from the other images.

Claims

1. A computer-implemented method for identifying objects in an image, comprising:

capturing an image using a camera;

generating a map that defines a spatial arrangement between objects found proximate to the camera and provides a unique identifier for each object in the map;

detecting objects in the image using feature extraction methods;

identifying the objects detected in the image using the map; and

tagging the objects detected in the image with the corresponding unique identifier for object obtained from the map.

2. The method of claim 1 further comprises computing distances between the objects based on wireless data transmissions between the objects and the camera;

and constructing the map from the positional information for the objects.

3. The method of claim 1 further comprises generating the map using unique identifiers received via a wireless data transmission from the objects.

4. The method of claim 1 further comprises importing the map to the camera from a location tracking system external from the camera.

5. The method of claim 1 further comprises extracting objects from the image using feature extraction methods and determining distances between the objects from the image data.

6. The method of claim 5 wherein determining distance between objects further comprises determining a focal length at which the image was captured and determining a conversion function between pixels in the image and a distance metric used to define the spatial arrangement between objects in the map.

7. The method of claim 1 wherein identifying the objects detected in the image further comprises determining a field of view at which the image was captured and determining possible groups of objects that could fall within the field of view of the camera.

8. The method of claim 7 further comprises computing distances between objects from a corresponding image for each possible group of object and computing a dissimilarity measure between the computed object distances and the map for each possible group of objects.

9. The method of claim 7 further comprises determining possible groups of objects by transposing the field of view onto the map and rotating the field of view in relation to the map.

10. The method of claim 1 further comprises identifying the objects in the image using data collected over a series of images taken by the camera.

11. The method of claim 1 further comprises identifying the objects in the image using features extracted from other images.

22. The method of claim 1 further comprises tagging the objects detected in the image with the corresponding unique identifier for object obtained from the map.

12. A computer-implemented method for identifying objects in an image, comprising:

capturing a series of images of a scene using a camera;

receiving a topographical map for the scene that defines distances between objects in the scene;

determining distances between objects in the scene from a given image;

approximating identities of objects in the given image by comparing the distances between objects as determined from the given image in relation to the distances between objects from the map; and

re-estimating identities of objects in the given image using features of the objects extracted from the other images.

13. The method of claim 12 further comprises generating the topographical map at the camera based wireless data transmissions with the objects

14. The method of claim 12 further comprises importing the map to the camera from a location tracking system external from the camera.

15. The method of claim 12 further comprises receiving a series of topographical maps such that each map correlates to one of the images and represents the scene when the corresponding image was captured by the camera.

17. The method of claim 12 wherein determining distance between objects further comprises determining a focal length at which the image was captured and determining a conversion function between pixels in the image and a distance metric.

18. The method of claim 12 wherein determining distance between objects further comprises:

determining a field of view at which the given image was captured;

determining possible groups of objects in the given image that could fall within the field of view of the camera; and

computing distances between objects in a given image for each possible group of objects.

19. The method of claim 18 wherein approximating identities further comprises, for each possible group of objects, computing a dissimilarity measure between the distances between objects as determined from the given image and the distances provide by the map;

and identifying the objects using the group having a lowest dissimilarity measure.

20. The method of claim 12 further comprises re-estimating identities of objects in the given image using features of the objects extracted from other images.

21. The method of claim 20 further comprises re-estimating identities of objects in the given image by maximizing a likelihood between features of objects extracted from the given image with features of corresponding objects from other images.

16. The method of 12 further comprises extracting features of the objects from the given image using a Haar classifier and determining distances between the objects based on the extracted features.