Object classification system for a vehicle

• US 20050273212A1
• Filed: 06/07/2004
• Published: 12/08/2005
• Est. Priority Date: 06/07/2004
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Hougen, Darrell
• Granted Patent: US 7,702,425 B2
• Time in Patent Office: Days
• US Class Current: 701/1
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 2201/08 Detecting or categorising vehicles

Abstract

A method of classifying objects within a vehicle (12) includes the detection of an object and the generation of an object detection signal in response to that detection. A range signal is generated in response to the object detection signal. An image detection signal is generated having an image representation of the object. The object detection signal is projected on an image plane (122) in response to the image detection signal to generate a fused image reference (120). A search region (144) is generated on the image plane (122) in the vicinity of fused image reference (120). A vector of feature values is calculated via generation of a sum-array (152) and in response to the range signal and the image detection signal. The search region (144) is classified in response to the vector of feature values.

Claims

1. A method of classifying objects within a vehicle comprising:

detecting at least one object and generating at least one object detection signal in response to said detection;

generating at least one range signal in response to said at least one object detection signal;

generating at least one image detection signal comprising an image representation of said at least one object;

projecting said at least one object detection signal on an image plane in response to said at least one image detection signal to generate at least one fused image reference;

generating at least one search region on said image plane in vicinity of each of said at least one fused image reference;

calculating at least one vector of feature values via generation of at least one sum-array and in response to said at least one range signal and said at least one image detection signal; and

classifying each of said at least one search region in response to said at least one vector of feature values.

2. A method as in claim 1 wherein said at least one vector of feature values is calculated using a plurality of functions.

3. A method as in claim 2 wherein said plurality of functions are formed in response to double-window parameters.

4. A method as in claim 3 wherein said double-window parameters comprise at least one parameter selected from pixel intensity values, pixel contrast values between windows, and edge values.

5. A method as in claim 2 wherein said plurality of functions comprise a common set of parameters selected from at least one of attributed data, inner window specifications, outer window specifications.

6. A method as in claim 5 wherein said attributed data comprises a set of sum-arrays.

7. A method as in claim 6 wherein said set of sum-arrays are formed in response to a set of features selected from at least one of intensity data, squared intensity data, x-derivative data, and y-derivative data.

8. A method as in claim 1 wherein said at least one vector of feature values is generated in response to at least one feature definition file.

9. A method as in claim 1 wherein said at least one vector of feature values is generated in response to at least one feature definition file using a single feature evaluation function.

10. A method as in claim 9 wherein said use of said single feature evaluation function comprises comparing two portions of said at least one search region with corresponding values within said at least one feature definition file.

11. A method as in claim 1 further comprising:

scoring each of said at least one search region to generate at least one classification score; and

performing at least one countermeasure in response to said at least one classification score.

12. An object classification system for a vehicle comprising:

at least one non-vision object detection sensor detecting at least one object and generating at least one object detection signal and at least one range signal in response to said detection;

at least one image-generating sensor generating at least one image detection signal comprising an image representation of said at least one object;

a fusion device projecting said at least one object detection signal on an image plane in response to said at least one image detection signal to generate at least one fused image reference;

a search region generator generating at least one search region on said image plane in vicinity of each of said at least one fused image reference;

a feature vector calculator calculating at least one vector of feature values via generation of at least one sum-array and in response to said at least one range signal and said at least one image detection signal; and

an object classifier classifying each of said at least one search region in response to said at least one vector of feature values.

13. A system as in claim 12 wherein said feature vector calculator uses a plurality of functions in calculating said at least one vector of feature values.

14. A system as in claim 13 wherein said plurality of functions are formed in response to double-window parameters.

15. A system as in claim 13 wherein said plurality of functions comprise a common set of parameters selected from at least one of attributed data, inner window specifications, outer window specifications.

16. A system as in claim 12 wherein said feature vector calculator generates said at least one vector of feature values in response to at least one feature definition file.

17. A system as in claim 12 wherein said feature vector calculator generates said at least one vector of feature values in response to at least one feature definition file using a single feature evaluation function.

18. A method of operating a collision warning and countermeasure system of a vehicle comprising:

detecting at least one object and generating at least one object detection signal in response to said detection;

generating at least one range signal in response to said at least one object detection signal;

generating at least one image detection signal comprising an image representation of said at least one object;

projecting said at least one object detection signal on an image plane in response to said at least one image detection signal to generate at least one fused image reference;

generating at least one search region on said image plane in vicinity of each of said at least one fused image reference;

calculating at least one vector of feature values via generation of at least one sum-array and in response to said at least one range signal and said at least one image detection signal;

classifying each of said at least one search region in response to said at least one vector of feature values;

scoring each of said at least one search region to generate at least one classification score; and

performing at least one countermeasure in response to said at least one classification score.

19. A method as in claim 18 further comprising incrementing a classification value upon consistent classification of said at least one object.

20. A method as in claim 18 further comprising selectively determining at least one point near a center of said at least one object, which is consistent with a potential threatening object.