THREE-DIMENSIONAL OBJECT DETECTION DEVICE, AND THREE-DIMENSIONAL OBJECT DETECTION METHOD

• US 20150324972A1
• Filed: 07/26/2013
• Published: 11/12/2015
• Est. Priority Date: 07/27/2012
• Status: Active Grant

• Current Assignee: Clarion Co., Ltd. (Faurecia SA), Nissan Motor Co., Ltd.
• Original Assignee: Clarion Co., Ltd. (Faurecia SA), Nissan Motor Co., Ltd.
• Inventors: HAYAKAWA, Yasuhisa, FUKATA, Osamu, MURAMATSU, Shoji, TAKEMURA, Masayuki, UTAGAWA, Akira, IRIE, Kota
• Granted Patent: US 9,558,546 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/10152 Varying illumination
• CPC Class Codes: G06T 2207/20224 Image subtraction
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 7/0008 checking presence/absence
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• 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 20/64 Three-dimensional objects
• CPC Class Codes: H04N 7/183 for receiving images from a single remote source

Abstract

A three-dimensional object detection device has an image capturing unit, an object detection unit, a nighttime assessment unit, a luminance detection unit, a luminance peak detection unit and a controller. The image capturing unit captures images rearward of a vehicle. The object detection unit detects a presence of an object from the captured images. The nighttime assessment unit assesses if nighttime has fallen. The luminance detection unit detects a luminance of image areas from the captured image. The luminance peak detection unit detects a peak in the luminance having a luminance gradient that is greater than or equal to a predetermined reference value from among the detected peaks in the luminance as a target luminance peak. The controller controls detection of the object in an image area in which the target luminance peak is detected when an assessment has been made that nighttime has fallen by the nighttime assessment unit.

Claims

2. A three-dimensional object detection device comprising:

an image capturing device mounted on a host vehicle, and comprising a lens for capturing images behind the host vehicle;

an image conversion unit programmed to perform viewpoint conversion of the captured images obtained by the image capturing device into bird'"'"'s-eye view images;

the three-dimensional object detection unit being programmed to detect a presence of a three-dimensional object based on differential waveform information in which the differential waveform information is generated by aligning in bird'"'"'s-eye view positions of the bird'"'"'s-eye view images obtained at different times by the image conversion device, and by counting a number of pixels that indicate a predetermined difference in a difference image of aligned bird'"'"'s-eye view images to form a frequency distribution;

a nighttime assessment unit programmed to assess whether or not nighttime has fallen;

a luminance detection unit programmed to detect a luminance of a plurality of image areas based on the captured images;

a luminance peak detection unit programmed to detect a peak in the luminance having a luminance gradient that is greater than or equal to a predetermined reference value from among the peaks in the luminance detected by the luminance detection unit as a target luminance peak; and

a controller programmed to control detection of the three-dimensional object by the three-dimensional object detection unit in an image area in which the target luminance peak is detected when an assessment has been made that nighttime has fallen by the nighttime assessment unit.

3. The three-dimensional object detection device according to claim 2, wherein

the three-dimensional object detection unit is further programmed to generate the differential waveform information by counting a number of pixels that indicate a difference of equal to or greater than a predetermined first threshold value to form the frequency distribution, and three-dimensional object detection unit detects the three-dimensional object on the difference image of the bird'"'"'s-eye view image based on the differential waveform when the peak value of the differential waveform information is equal to or greater than a predetermined second threshold value;

and

the controller is further programmed to suppress the detection of the three-dimensional object by the three-dimensional object detection unit based on a result of detecting the target luminance peak by changing one of the first threshold value and the second threshold value to a higher value.

4. The three-dimensional object detection device according to claim 2, wherein

when the three-dimensional object detection unit generates the differential waveform information, the controller is further programmed to cause the three-dimensional object detection unit to calculate the value obtained by counting a number of pixels that indicate the predetermined difference in the difference image of the bird'"'"'s-eye view images to form the frequency distribution to lower, thereby suppressing the detection of the three-dimensional object by the three-dimensional object detection unit.

5. A three-dimensional object detection device comprising:

an image capturing device mounted on a host vehicle, and comprising a lens for capturing images behind the vehicle;

an image conversion unit programmed to perform viewpoint conversion of the captured images obtained by the image capturing device into bird'"'"'s-eye view images;

the three-dimensional object detection unit programmed to detect a presence of a three-dimensional object based on edge information that is detected from the bird'"'"'s-eye view images obtained by the image conversion unit;

a nighttime assessment unit programmed to assess whether or not nighttime has fallen;

a luminance detection unit programmed to detect a luminance of a plurality of image areas based on the captured images;

a luminance peak detection unit programmed to detect a peak in the luminance having a luminance gradient that is greater than or equal to a predetermined reference value from among the peaks in the luminance detected by the luminance detection unit as a target luminance peak; and

a controller programmed to control detection of the three-dimensional object by the three-dimensional object detection unit in an image area in which the target luminance peak is detected when an assessment has been made that nighttime has fallen by the nighttime assessment unit.

6. The three-dimensional object detection device according to claim 5, wherein

the three-dimensional object detection unit is further programmed to detect edge components that have a luminance difference between adjacent pixel areas of equal to or greater than a predetermined first threshold value based on the bird'"'"'s-eye view images and to detect the three-dimensional object based on the edge information when a quantity of the edge information based on the edge components is equal to or greater than a predetermined second threshold value;

and

the controller is further programmed to suppress the detection of the three-dimensional object by the three-dimensional object detection unit based on a result of detecting the target luminance peak by changing one of the first threshold value and the second threshold value to a higher value.

7. The three-dimensional object detection device according to claim 5, wherein

the controller is further programmed to suppress the detection of the three-dimensional object by the three-dimensional object detection unit when the three-dimensional object detection unit detects the edge information by causing the three-dimensional object detection unit to output the edge information as low.

9-1. The three-dimensional object detection device according to claim 1, further comprising:

a lens state assessment unit programmed to assess a degree of pollution of the lens based on the captured images, wherein

the controller being further programmed to set the suppression degree to be higher when suppressing the detection of the three-dimensional object with higher amounts of pollution by promoting the detection of the target luminance peak by the luminance peak detection unit.

18. A three-dimensional object detection method comprising:

converting viewpoints of captured images into bird'"'"'s-eye view images;

aligning positions of the bird'"'"'s-eye view images that are obtained at different times are in a bird'"'"'s-eye view;

generating differential waveform information by counting a number of pixels that indicate a predetermined difference in a difference image of aligned bird'"'"'s-eye view images to form a frequency distribution;

detecting a presence of a three-dimensional object based on the differential waveform information;

determining whether or not nighttime has fallen;

detecting a luminance in a plurality of image areas based on the captured images;

detecting a peak in the luminance having a luminance gradient of a predetermined value or more, from among the detected peaks in the luminance, as a target luminance peak; and

suppressing the detection of the three-dimensional object in an image area in which the target luminance peak is detected when an assessment has been made that nighttime has fallen.

19. A three-dimensional object detection method comprising:

converting viewpoints of captured images into bird'"'"'s-eye view images;

detecting edge information from the bird'"'"'s-eye view images; and

detecting a presence of a three-dimensional object based on the edge information;

determining whether or not nighttime has fallen;

detecting a luminance in a plurality of image areas based on the captured images;

detecting a peak in the luminance having a luminance gradient of a predetermined value or more, from among the detected peaks in the luminance, as a target luminance peak; and

suppressing the detection of the three-dimensional object in an image area in which the target luminance peak is detected when an assessment has been made that nighttime has fallen.