THREE-DIMENSIONAL OBJECT DETECTION DEVICE
First Claim
1. A three-dimensional object detection device comprising:
- an imaging unit configured to be installed on a vehicle to capture images of a region at a rear of the vehicle;
an image conversion unit configured to convert a viewpoint of the images obtained by the imaging unit to bird'"'"'s-eye view images;
a differential waveform information creating unit configured to create differential waveform information by positionally aligning the bird'"'"'s-eye view images of different times obtained by the image conversion unit within a bird'"'"'s-eye view, the differential waveform information creating unit being further configured to create a frequency distribution of a number of pixels by counting the number of pixels representing a predetermined differential in a differential image of the bird'"'"'s-eye view images that were positionally aligned;
a three-dimensional object detection unit configured to detect three-dimensional objects which are included in the differential waveform information and which are present in detection areas set in left and right rear sides of the vehicle, based on the frequency distribution of the number of pixels representing the predetermined differential in the differential image along a direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted; and
a natural object assessment unit programmed to calculate an irregularity evaluation value for evaluating an irregularity of the differential waveform information based on a first pixel number of first pixels representing a first predetermined differential in the differential image containing the three-dimensional object that was detected, and a second pixel number of second pixels that have been extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted and that represent a second predetermined differential greater than the first predetermined differential in the differential image, and the natural object assessment unit configured to assess that the three-dimensional object detected by the three-dimensional object detection unit is a natural object including plants or snow present along a lane traveled by the vehicle when the calculated irregularity evaluation value is equal to or greater than a predetermined irregularity evaluation threshold set in advance.
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Accused Products
Abstract
A three-dimensional object detection device basically includes a three-dimensional object detection unit, a natural object assessment unit and a control unit. The three-dimensional object detection unit detects three-dimensional objects based on image information of a rear of a vehicle from a camera. The natural object assessment unit assesses that a detected three-dimensional object is a natural object, such as a plant or snow, based on an irregularity evaluation value calculated based on a first pixel number of first pixels representing a first predetermined differential in the differential image containing the detected three-dimensional object and a second pixel number of second pixels corresponding to the three-dimensional object and representing a second predetermined differential greater than the first predetermined differential.
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Citations
26 Claims
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1. A three-dimensional object detection device comprising:
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an imaging unit configured to be installed on a vehicle to capture images of a region at a rear of the vehicle; an image conversion unit configured to convert a viewpoint of the images obtained by the imaging unit to bird'"'"'s-eye view images; a differential waveform information creating unit configured to create differential waveform information by positionally aligning the bird'"'"'s-eye view images of different times obtained by the image conversion unit within a bird'"'"'s-eye view, the differential waveform information creating unit being further configured to create a frequency distribution of a number of pixels by counting the number of pixels representing a predetermined differential in a differential image of the bird'"'"'s-eye view images that were positionally aligned; a three-dimensional object detection unit configured to detect three-dimensional objects which are included in the differential waveform information and which are present in detection areas set in left and right rear sides of the vehicle, based on the frequency distribution of the number of pixels representing the predetermined differential in the differential image along a direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted; and a natural object assessment unit programmed to calculate an irregularity evaluation value for evaluating an irregularity of the differential waveform information based on a first pixel number of first pixels representing a first predetermined differential in the differential image containing the three-dimensional object that was detected, and a second pixel number of second pixels that have been extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted and that represent a second predetermined differential greater than the first predetermined differential in the differential image, and the natural object assessment unit configured to assess that the three-dimensional object detected by the three-dimensional object detection unit is a natural object including plants or snow present along a lane traveled by the vehicle when the calculated irregularity evaluation value is equal to or greater than a predetermined irregularity evaluation threshold set in advance. - View Dependent Claims (3, 4, 5, 6, 8, 9, 10, 13, 15, 16, 17)
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2. A three-dimensional object detection device comprising:
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an imaging unit configured to be installed on a vehicle to capture images of a region at a rear of the vehicle; an image conversion unit configured to convert a viewpoint of the images obtained by the imaging unit to bird'"'"'s-eye view images; an edge information creating unit configured to create edge information by extracting pixels in which a luminance difference of adjacent image areas is equal to or greater than a predetermined threshold in the bird'"'"'s-eye view images obtained by the image conversion unit; a three-dimensional object detection unit configured to detect three-dimensional objects which are included in the edge information and which are present in detection areas set in left and right rear sides of the vehicle, based on the edge information including the pixels that are extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view image is viewpoint-converted and that have a luminance difference of adjacent image areas equal to or greater than the predetermined threshold; and a natural object assessment unit programmed to calculate an irregularity evaluation value for evaluating an irregularity of the edge information based on a first pixel number of first pixels in which the luminance difference of the adjacent image areas in the bird'"'"'s-eye images containing the three-dimensional object that was detected is equal to or greater than a first predetermined threshold, and a second pixel number of second pixels that have been extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted and in which the luminance difference of adjacent image areas in the bird'"'"'s-eye images is equal to or greater than a second predetermined threshold greater than the first predetermined threshold, and the natural object assessment unit configured to assess that the three-dimensional object detected by the three-dimensional object detection unit is a natural object including plants or snow present along a lane traveled by the vehicle when the calculated irregularity evaluation value is equal to or greater than a predetermined irregularity evaluation threshold set in advance. - View Dependent Claims (7, 11, 12, 14, 20, 21, 22, 23, 24, 25, 26)
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18. A three-dimensional object detection method comprising:
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converting viewpoint images of region at a rear of a vehicle to bird'"'"'s-eye view images; creating differential waveform information by aligning the bird'"'"'s-eye view images of different times within a bird'"'"'s-eye view, and creating a frequency distribution of a number of pixels by counting the number of pixels representing a predetermined differential in a differential image of the bird'"'"'s-eye view images that were positionally aligned; detecting three-dimensional objects which are included in the differential waveform information and which are present in detection areas set in left and right rear sides of the vehicle, based on the frequency of the number of pixels representing the predetermined differential in the differential image along a direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted; and calculating an irregularity evaluation value for evaluating an irregularity of the differential waveform information based on a first pixel number of first pixels representing a first predetermined differential in the differential image containing the three-dimensional object that was detected, and a second pixel number of second pixels that have been extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view an viewpoint-converted and that represent a second predetermined differential greater than the first predetermined differential in the differential image, and assessing that the three-dimensional object that was detected is a natural object including plants or snow present along the lane traveled by the vehicle when the calculated irregularity evaluation value is equal to or greater than a predetermined irregularity evaluation threshold set in advance.
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19. A three-dimensional object detection method comprising:
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converting viewpoint images of region at a rear of a vehicle to bird'"'"'s-eye view images; creating edge information by extracting pixels in which a luminance difference of adjacent image areas is equal to or greater than a predetermined threshold in the bird'"'"'s-eye view images that were obtained; detecting three-dimensional objects which are included in the edge information and which are present in detection areas set in left and right rear sides of the vehicle, based on the edge information including the pixels that are extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view image is viewpoint-converted and that have a luminance difference of adjacent image areas equal to or greater than the predetermined threshold; and calculating an irregularity evaluation value for evaluating the irregularity of the edge information based on a first pixel number of first pixels in which the luminance difference of adjacent image areas in the bird'"'"'s-eye image containing the three-dimensional object that was detected is equal to or greater than a first predetermined threshold, and a second pixel number of second pixels that have been extracted along the direction in which the three-dimensional object falls when the bird'"'"'s-eye view images are viewpoint-converted and in which the luminance difference of adjacent image areas in the bird'"'"'s-eye image is equal to or greater than a second predetermined threshold greater than the first predetermined threshold, and for assessing that the three-dimensional object that was detected is a natural object including plants or snow present along the lane traveled by the vehicle when the calculated irregularity evaluation value is equal to or greater than a predetermined irregularity evaluation threshold set in advance.
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Specification