FUSION-BASED OBJECT-RECOGNITION

• US 20150363643A1
• Filed: 06/16/2015
• Published: 12/17/2015
• Est. Priority Date: 06/16/2014
• Status: Active Grant

• Current Assignee: AGT International GMBH
• Original Assignee: AGT International GMBH
• Inventors: HUBER, Marco, MERENTITIS, Andreas, HEREMANS, Roel, DEBES, Christian
• Granted Patent: US 9,721,162 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 18/25 Fusion techniques
• CPC Class Codes: G06F 18/254 of classification results, e.g. of results related to same input data
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/20221 Image fusion; Image merging

Abstract

An object-recognition method and system employing Bayesian fusion algorithm to reiteratively improve probability of correspondence between captured object images and database object images by fusing probability data associated with each of plurality of object image captures.

Claims

1. A fusion-based method of object recognition comprising:

capturing a first object image with an image capture device;

generating a first score indicative of a probability that the first object image corresponds to a data base image; and

using a processor to apply a Bayesian fusion algorithm to revise the probability based on a second score of a second object image captured by an image capture device.

2. The fusion-based method of claim 1, wherein the processor is further configured to use credibility ratings associated with the first object image and the second object image to revise the first probability.

3. The fusion-based method of claim 1, wherein the processor is further configured to apply a transition model to a capture time of the first object image and a capture time of the second object image to revise the first probability.

4. A fusion-based, object-recognition system comprising:

a plurality of image capture devices, each of the image capture devices configured to generate a score indicative of probability of correspondence between an object image it captured and an image in a data base;

a processor configured to apply a Bayesian fusion algorithm to revise the probability based on a second score of a second object image captured by an image capture device.

5. The fusion-based object-recognition system of claim 4, wherein the processor is further configured to use credibility ratings associated with the first object image and the second object image to revise the probability.

6. The fusion-based object-recognition system of claim 4, wherein the processor is further configured to apply a transition model to a capture time of the first object image and a capture time of the second object image to revise the probability.