Abstract: An image processing device includes a detector, a setting unit, a calculator, an estimator, and a determining unit. The detector sets a three-dimensional object region by detecting a three-dimensional object. The setting unit sets a first image region corresponding to the three-dimensional object region, a second image region including a left end of and partly overlapping the first image region, and a third image region including a right end of and partly overlapping the first image region. The calculator calculates representative values of parallax-related values in pixel columns in the image regions, and calculates an approximate line of the representative values in each of the image regions. The estimator estimates a continuous structure degree, from a slope value of the approximate line of each of the image regions. The determining unit determines whether the three-dimensional object is a vehicle, from the continuous structure degree.

Abstract: A vehicle exterior environment recognition apparatus includes first and second width derivation units, a degree-of-overlap derivation unit, and a specific object determination unit. The first width derivation unit derives a first width of a first three-dimensional object based on a luminance image. The second width derivation unit derives a second width of a second three-dimensional object based on a distance image. The degree-of-overlap derivation unit obtains an overlap width with which the first and second widths overlap horizontally, and set, as a degree of overlap, whichever is greater out of a value obtained by dividing the overlap width by the first width and a value obtained by dividing the overlap width by the second width. The specific object determination unit determines that the first and second three-dimensional objects are an identical specific object, on the condition that the degree of overlap is greater than a predetermined threshold.

Abstract: An image processing apparatus includes an extractor and an object identifier. The extractor is configured to extract a feature quantity included in a captured image. The object identifier is configured to perform identification of an object on the basis of the feature quantity. The extractor is configured to extract the feature quantity by performing, on the captured image, a convolution calculation multiple times using a filter including multiple filter values that are two-dimensionally arranged. The multiple filter values are initially set at values that are line-symmetric with respect to an axis of symmetry along a predetermined direction. Augmentation batch data of learning data to be used in an update process of the filter by machine learning is configured to include any unflipped image extracted and a flipped image as paired images, the flipped image resulting from applying image-flipping to the unflipped image with respect to the axis of symmetry.

Abstract: A vehicle external environment recognition apparatus includes at least one processor, and at least one memory coupled to the at least one processor. The at least one processor is configured to operate in cooperation with at least one program stored in the at least one memory to execute processing. The processing includes generating a distance image from luminance images, specifying, by using semantic segmentation, a floating matter class in the luminance images, and invalidating parallax associated with floating pixels that are included in the distance image and belong to the floating matter class.

Abstract: An image processing device includes a detector, a setting unit, a calculator, an estimator, and a determining unit. The detector sets a three-dimensional object region by detecting a three-dimensional object. The setting unit sets a first image region corresponding to the three-dimensional object region, a second image region including a left end of and partly overlapping the first image region, and a third image region including a right end of and partly overlapping the first image region. The calculator calculates representative values of parallax-related values in pixel columns in the image regions, and calculates an approximate line of the representative values in each of the image regions. The estimator estimates a continuous structure degree, from a slope value of the approximate line of each of the image regions. The determining unit determines whether the three-dimensional object is a vehicle, from the continuous structure degree.

Abstract: A vehicle exterior environment recognition apparatus includes first and second width derivation units, a degree-of-overlap derivation unit, and a specific object determination unit. The first width derivation unit derives a first width of a first three-dimensional object based on a luminance image. The second width derivation unit derives a second width of a second three-dimensional object based on a distance image. The degree-of-overlap derivation unit obtains an overlap width with which the first and second widths overlap horizontally, and set, as a degree of overlap, whichever is greater out of a value obtained by dividing the overlap width by the first width and a value obtained by dividing the overlap width by the second width. The specific object determination unit determines that the first and second three-dimensional objects are an identical specific object, on the condition that the degree of overlap is greater than a predetermined threshold.