Abstract: A parallax calculating apparatus comprises first parallax calculating means for calculating a first parallax on a basis of a reference image for all pixels in the reference image using SGM method, second parallax calculating means for calculating a second parallax on a basis of the reference image for at least a part of pixels among pixels in the reference image using BM method, and final parallax calculating means for calculating a final parallax of each of pixels in the reference image based on the first and second parallaxes. The final parallax calculating means calculates the first parallax as the final parallax for a pixel for which only the first parallax has been calculated and calculates a parallax where a decimal part of the first parallax is replaced with that of the second parallax as the final parallax for a pixel for which the first and second parallaxes have been calculated.

Abstract: The distance measuring device detects parallax between right and left captured images where a front object is present ahead of the own vehicle, and calculate a parallax distance between the front object and the own vehicle. The radar device detects a radar detected distance therebetween. The distance measuring device calculates a parallax error based on the difference between the parallax calculated distance and the radar detected distance. A correction region is set in the right captured image and divided into correction divided regions. The distance measuring device sets an individual correction parallax for every correction divided regions, based on the parallax error and the identified correction divided regions.

Abstract: A parallax calculating apparatus comprises first parallax calculating means for calculating a first parallax on a basis of a reference image for all pixels in the reference image using SGM method, second parallax calculating means for calculating a second parallax on a basis of the reference image for at least a part of pixels among pixels in the reference image using BM method, and final parallax calculating means for calculating a final parallax of each of pixels in the reference image based on the first and second parallaxes, The final parallax calculating means calculates the first parallax as the final parallax for a pixel for which only the first parallax has been calculated and calculates a parallax where a decimal part of the first parallax is replaced with that of the second parallax as the final parallax for a pixel for which the first and second parallaxes have been calculated,

Abstract: In a position measuring apparatus, a correspondence point detector detects, for each set of images at a respective one of time instants, correspondence points from the respective images of the set, where the correspondence points are points on respective image planes representing the same three-dimensional position. A projection point calculator calculates a projection point of each of the correspondence points detected at the respective time instants onto each of a plurality of common planes set at different depthwise positions in a world coordinate system using preset camera parameters. A reconstruction point calculator calculates a point at which distances to a plurality of rays each connecting the projection points of the correspondence point on a respective one of the image planes onto the plurality of common planes are minimized, as a reconstruction point representing a three-dimensional position of the correspondence point.

Abstract: A distance detection device calculates a pixel cost, every reference pixel, based on a difference between reference pixel information in a reference image and comparative pixel information in a comparative image while switching the reference and comparative images. The device calculates a parallax cost, every reference pixel, representing a cost regarding a change-amount of the parallax as a coordinate difference between a reference pixel and a comparative pixel when the reference image is switched. The device calculates a combination of each reference pixel and a comparative pixel having a minimum total cost every reference pixel. The minimum total cost represents a sum of the pixel cost and the parallax cost. The device obtains a relationship of a corresponding point between each reference pixel and its corresponding comparative pixel, and calculates a distance to an object in each captured image based on the relationship of the corresponding point.

Abstract: A position measuring apparatus detects, from respective first and second imaging planes of first and second captured images, first and second corresponding points estimated to represent a common three-dimensional position. The apparatus calculates first to fourth projected points. Each of the first and second projected points represents a projected point of the first corresponding point on a corresponding one of the first and second common planes. Each of the third and fourth projected points represents a projected point of the second corresponding point on a corresponding one of the first and second common planes. The apparatus calculates a first beam connecting the first and second projected points, a second beam connecting the third and fourth projected points, and a point having a minimum square distance relative to each of the first and second beams as a restored point representing the three-dimensional position of the first and second corresponding points.

Abstract: A corresponding point searching method searches corresponding points in plural images, acquired by in-vehicle cameras, for each pixel in a reference image by using a predetermined first method, for example, the Viterbi algorithm. The method searches corresponding points in the plural images for each pixel in the reference image by using a predetermined second method, for example, an optical flow method. The method detects whether or not a search accuracy of the corresponding points in each region divided in the reference image obtained by the predetermined first method is not less than a reference value. When not less than the reference value, the method selects the corresponding points obtained by the predetermined first method. When less than the reference value, the searching method selects the corresponding points obtained by the predetermined second method. The searching method provides the corresponding points between the plural images with a high accuracy.

Abstract: The distance measuring device detects parallax between right and left captured images where a front object is present ahead of the own vehicle, and calculate a parallax distance between the front object and the own vehicle. The radar device detects a radar detected distance therebetween. The distance measuring device calculates a parallax error based on the difference between the parallax calculated distance and the radar detected distance. A correction region is set in the right captured image and divided into correction divided regions. The distance measuring device sets an individual correction parallax for every correction divided regions, based on the parallax error and the identified correction divided regions.

Abstract: An object detection apparatus includes a camera and an ECU. The camera is mounted to a vehicle and captures an image. The ECU is configured to obtain a depth distance for each pixel area of the image based on the image; extract at least one potential object based on the depth distance; calculate an amount of change over time in the depth distance of the at least one potential object; and detect an object around the vehicle from among the at least one potential object using the amount of change over time. When a first potential object and a second potential object that are adjacent in the image are extracted, and a second amount of change over time is twice a first amount of change over time, the second potential object is determined to be the same object as the first potential object.

Abstract: A position measuring apparatus detects, from respective first and second imaging planes of first and second captured images, first and second corresponding points estimated to represent a common three-dimensional position. The apparatus calculates first to fourth projected points. Each of the first and second projected points represents a projected point of the first corresponding point on a corresponding one of the first and second common planes. Each of the third and fourth projected points represents a projected point of the second corresponding point on a corresponding one of the first and second common planes. The apparatus calculates a first beam connecting the first and second projected points, a second beam connecting the third and fourth projected points, and a point having a minimum square distance relative to each of the first and second beams as a restored point representing the three-dimensional position of the first and second corresponding points.

Abstract: In an object detection apparatus and an object detection method, as first and second images, captured images of an area ahead of a vehicle in a vehicle advancing direction are acquired from first and second imaging units provided in the vehicle. Based on the first and second images, whether or not an object is present in a blind spot ahead of the vehicle in the vehicle advancing direction is determined. When the object is determined to be present in the blind spot, the first and second images are held in time series. As first and second image differences, differences in a feature quantity between a previous image and a current image in the first and second images are acquired. Based on the first and second image differences, whether or not the object is approaching the area ahead of the vehicle is determined.

Abstract: An object estimation apparatus estimates a position and a speed of an object in images based on the images taken by an image taking means from different positions.

Abstract: A recognition object detecting apparatus is provided which includes an imaging unit which generates image data representing a taken image, and a detection unit which detects a recognition object from the image represented by the image data. The imaging unit has a characteristic in which a relation between luminance and output pixel values varies depending on a luminance range. The detection unit binarizes the output pixel values of the image represented by the image data by using a plurality of threshold values to generate a plurality of binary images, and detects the recognition object based on the plurality of binary images.

Abstract: A parallax detection device receives right side image and a left side image, makes right and left low resolution images, and divides the right low resolution image into blocks composed of pixels. For every block, the device detects a parallax of the block by searching the block in the left low resolution image having the region the same as the region of the block of the right low resolution image by using a dynamic programming method. The device divides the right side image into blocks, and searches a resolution corresponding block in the left side image having the region the same as the region of the block for every block by using a block matching method to detect a parallax of the block. The device limits the searching range of the resolution corresponding block in the left side image based on the parallax detection result obtained by the dynamic programming method.

Abstract: A corresponding point searching method searches corresponding points in plural images, acquired by in-vehicle cameras, for each pixel in a reference image by using a predetermined first method, for example, the Viterbi algorithm. The method searches corresponding points in the plural images for each pixel in the reference image by using a predetermined second method, for example, an optical flow method. The method detects whether or not a search accuracy of the corresponding points in each region divided in the reference image obtained by the predetermined first method is not less than a reference value. When not less than the reference value, the method selects the corresponding points obtained by the predetermined first method. When less than the reference value, the searching method selects the corresponding points obtained by the predetermined second method. The searching method provides the corresponding points between the plural images with a high accuracy.

Abstract: An object detection apparatus includes a camera and an ECU. The camera is mounted to a vehicle and captures an image. The ECU is configured to obtain a depth distance for each pixel area of the image based on the image; extract at least one potential object based on the depth distance; calculate an amount of change over time in the depth distance of the at least one potential object; and detect an object around the vehicle from among the at least one potential object using the amount of change over time. When a first potential object and a second potential object that are adjacent in the image are extracted, and a second amount of change over time is twice a first amount of change over time, the second potential object is determined to be the same object as the first potential object.

Abstract: An object estimation apparatus estimates a position and a speed of an object in images based on the images taken by an image taking means from different positions.

Abstract: There is provided an apparatus for generating a disparity map. According to the apparatus, an image acquisition section acquires a right-camera image and a left-camera image which are picked up from mutually different viewpoints by cameras. A disparity map generation section generates a disparity map that includes disparity expressed in terms of a difference in pixel positions between each of pixels and a corresponding one of pixels in the right-camera image and the left-camera image, respectively, as acquired. A weight determination section determines a weight that serves as a degree of contribution to disparity correction, for each of weight-calculation-target pixels composed of surrounding pixels. The weight-calculation-target pixels include a correction-target pixel or surrounding pixels that are present around the correction-target pixel in the disparity map. A disparity map correction section corrects the disparity of the correction-target pixel, using weighted average based on the determined weight.

Abstract: A distance detection device calculates a pixel cost, every reference pixel, based on a difference between reference pixel information in a reference image and comparative pixel information in a comparative image while switching the reference and comparative images. The device calculates a parallax cost, every reference pixel, representing a cost regarding a change-amount of the parallax as a coordinate difference between a reference pixel and a comparative pixel when the reference image is switched. The device calculates a combination of each reference pixel and a comparative pixel having a minimum total cost every reference pixel. The minimum total cost represents a sum of the pixel cost and the parallax cost. The device obtains a relationship of a corresponding point between each reference pixel and its corresponding comparative pixel, and calculates a distance to an object in each captured image based on the relationship of the corresponding point.

Abstract: There is provided an apparatus for generating a disparity map. According to the apparatus, an image acquisition section acquires a right-camera image and a left-camera image which are picked up from mutually different viewpoints by cameras. A disparity map generation section generates a disparity map that includes disparity expressed in terms of a difference in pixel positions between each of pixels and a corresponding one of pixels in the right-camera image and the left-camera image, respectively, as acquired. A weight determination section determines a weight that serves as a degree of contribution to disparity correction, for each of weight-calculation-target pixels composed of surrounding pixels. The weight-calculation-target pixels include a correction-target pixel or surrounding pixels that are present around the correction-target pixel in the disparity map. A disparity map correction section corrects the disparity of the correction-target pixel, using weighted average based on the determined weight.