OBJECT DETECTION SYSTEM

• US 20180262739A1
• Filed: 03/10/2017
• Published: 09/13/2018
• Est. Priority Date: 03/10/2017
• Status: Abandoned Application

• Current Assignee: Denso International America Incorporated (DENSO Corporation)
• Original Assignee: Denso International America Incorporated (DENSO Corporation)
• Inventors: HUNT, Shawn
• Application Number:
  US15/455,656
• Publication Number:
  US 20180262739A1
• Time in Patent Office: Days
• CPC Class Codes: G01B 11/002 for measuring two or more coordinates
• CPC Class Codes: G01B 11/24 for measuring contours or curvatures
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/582 of traffic signs
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights
• CPC Class Codes: G06V 20/647 by matching two-dimensional images to three-dimensional objects
• CPC Class Codes: H04N 13/221 using the relative movement between cameras and objects
• CPC Class Codes: H04N 23/60 Control of cameras or camera modules

Abstract

A three-dimensional imaging system for imaging an object of interest present in an area about a vehicle. The system includes a camera and a control module. The camera is configured to capture an image of the area about the vehicle including the object of interest. A control module of the system compares the captured image to previously captured model images including examples of the object of interest. The control module also identifies the object of interest in the captured image based on the comparison, and builds a three-dimensional reconstruction of the object of interest.

Claims

1. A method for creating a three-dimensional reconstruction of an object of interest, the method comprising:

capturing an image of an area about a vehicle with a camera;

comparing the captured image to previously captured model images including examples of the object of interest;

identifying the object of interest in the captured image based on the comparison; and

building a three-dimensional reconstruction of the object of interest.

2. The method of claim 1, wherein the object of interest is a road sign.

3. The method of claim 1, wherein the object of interest is a traffic light.

4. The method of claim 1, wherein the object of interest is infrastructure.

5. The method of claim 1, wherein comparing the captured image to previously captured model images includes:

segmenting the captured image into regions having similar pixel characteristics;

obtaining image statistics for each one of the segmented regions, including the mean and standard deviation of pixel values in each one of the segmented regions; and

comparing the image statistics obtained from the captured image with model image statistics of areas of the previously captured model images including the examples of the object of interest.

6. The method of claim 5, wherein identifying the object of interest in the captured image includes:

identifying the segmented region of the captured image having image statistics that are most similar to, or the same as, the model image statistics for one or more segmented areas of the previously captured model images including the examples of the object of interest.

7. The method of claim 6, wherein building the three-dimensional reconstruction of the object of interest includes:

building a three-dimensional reconstruction of the segmented region of the captured image having image statistics that are most similar to, or the same as one or more of, the model image statistics of the previously captured model images including the examples of the object of interest.

8. The method of claim 1, wherein the three-dimensional reconstruction of the object includes only the object of interest.

9. A three-dimensional imaging system for imaging an object of interest present in an area about a vehicle, the system comprising:

a camera configured to capture an image of the area about the vehicle including the object of interest; and

a control module that;

compares the captured image to previously captured model images including examples of the object of interest;

identifies the object of interest in the captured image based on the comparison; and

builds a three-dimensional reconstruction of the object of interest.

10. The method of claim 9, wherein the object of interest is a road sign.

11. The method of claim 9, wherein the object of interest is a traffic light.

12. The method of claim 9, wherein the object of interest is infrastructure.

13. The method of claim 9, wherein when comparing the captured image to previously captured model images, the control module:

segments the captured image into regions having similar pixel characteristics;

obtains image statistics for each one of the segmented regions, including the mean and standard deviation of pixel values in each one of the segmented regions; and

compares the image statistics obtained from the captured image with model image statistics of areas of the previously captured model images including the examples of the object of interest.

14. The method of claim 13, wherein when identifying the object of interest in the captured image, the control module:

identifies the segmented region of the captured image having image statistics that are most similar to, or the same as, the model image statistics for one or more segmented areas of the previously captured model images including the examples of the object of interest.

15. The method of claim 14, wherein when building the three-dimensional reconstruction of the object, the control module:

builds a three-dimensional reconstruction of the segmented region of the captured image having image statistics that are most similar to, or the same as, one or more of the model image statistics of the previously captured model images including the examples of the object of interest.

16. The method of claim 9, wherein the control module builds a three-dimensional reconstruction of only the object of interest such that the three-dimensional reconstruction does not include other objects of the captured image.