A three-dimensional object detection device comprising: imaging means configured for being installed on a vehicle for imaging the rear of the vehicle; image conversion means for converting the viewpoint of an image obtained by the imaging means to a bird's-eye view image; three-dimensional object detection means (32, 33) for creating differential waveform information by aligning the positions of bird's-eye view images of different times obtained by the image conversion means within a bird's-eye view, and counting and creating a frequency distribution of the number of pixels representing a predetermined differential in a differential image of the positionally aligned bird's-eye view images; three-dimensional object detection means for detecting three-dimensional objects from the differential waveform information and which are present in detection areas (A1, A2) set in the left and right sides to the rear of the vehicle, based on the counted frequency of the number of pixels representing a predetermined differential in a differential image along the direction in which three-dimensional objects fall into the bird's eye view image when the bird's-eye view images are created by the image conversion means, said falling obtained by viewing the image from a viewpoint of an imaginary camera looking vertically downward; and natural object assessment means for 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 detected three-dimensional object, 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 image is created by the image conversion means, that represent a second predetermined differential greater than the first predetermined differential in the differential image, and that constitute a pixel group aligned along the falling direction in at least a predetermined amount, the second pixels corresponding to manmade three-dimensional objects, wherein the first pixels comprise the second pixels and pixels that correspond to natural three-dimensional objects and are detected to be aligned irregularly, and for assessing that the three-dimensional object detected by the three-dimensional object detection means is a natural object being 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. imaging means configured for being installed on a vehicle for imaging the rear of the vehicle; image conversion means for converting the viewpoint of an image obtained by the imaging means to a bird's-eye view image; three-dimensional object detection means (32, 33) for creating differential waveform information by aligning the positions of bird's-eye view images of different times obtained by the image conversion means within a bird's-eye view, and counting and creating a frequency distribution of the number of pixels representing a predetermined differential in a differential image of the positionally aligned bird's-eye view images; three-dimensional object detection means for detecting three-dimensional objects from the differential waveform information and which are present in detection areas (A1, A2) set in the left and right sides to the rear of the vehicle, based on the counted frequency of the number of pixels representing a predetermined differential in a differential image along the direction in which three-dimensional objects fall into the bird's eye view image when the bird's-eye view images are created by the image conversion means, said falling obtained by viewing the image from a viewpoint of an imaginary camera looking vertically downward; and natural object assessment means for 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 detected three-dimensional object, 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 image is created by the image conversion means, that represent a second predetermined differential greater than the first predetermined differential in the differential image, and that constitute a pixel group aligned along the falling direction in at least a predetermined amount, the second pixels corresponding to manmade three-dimensional objects, wherein the first pixels comprise the second pixels and pixels that correspond to natural three-dimensional objects and are detected to be aligned irregularly, and for assessing that the three-dimensional object detected by the three-dimensional object detection means is a natural object being 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.