Abstract: A self-position estimation method includes: detecting a relative position of a target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a behavior change amount of the moving body; selecting, from among the accumulated target position data, the target position data of the relative position detected during a period in which the behavior change amount is less than a threshold value; and collating the selected target position data with map information indicating a position on a map of the target to estimate a present position of the moving body.

Abstract: A self-position estimation method includes: detecting a relative position of each target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a slope amount of a traveling road of the moving body; selecting, from among the accumulated target position data, the target position data of one or more targets in one or more sections having a slope amount less than a threshold value; and collating the selected target position data with map information indicating positions of the targets on a two-dimensional map to estimate a present position of the moving body.

Abstract: A step detection device detects the distance and the direction to a road surface around a vehicle, using a distance sensor mounted on the vehicle, and sets a first step determination position and a second step determination position on the road surface. Then, the step detection device calculates the height changes of the road surfaces at the first step determination position and the second step determination position based on the distance and the direction to the road surface, and detects a step on the road surface based on one of the step determination positions, the gradient of the height change of the road surface at the one being larger.

Abstract: Multiple objects detected by multiple sensors are subjected to a determination as to whether or not the objects are identical to each other. If there is an object in the multiple objects, of which object position becomes undetectable after the point when the multiple objects detected by the multiple sensors are determined to be the identical object, a determination is made as to whether or not the continuously detected object is an object identical to the object in a previous processing based on a predicted range calculated from a previously detected object position of the object becoming undetectable, and on a range of presence estimated from an object position of the continuously detected object.

Abstract: Multiple objects detected by multiple sensors are subjected to a determination as to whether or not the objects are identical to each other. If there is an object in the multiple objects, of which object position becomes undetectable after the point when the multiple objects detected by the multiple sensors are determined to be the identical object, a determination is made as to whether or not the continuously detected object is an object identical to the object in a previous processing based on a predicted range calculated from a previously detected object position of the object becoming undetectable, and on a range of presence estimated from an object position of the continuously detected object.

Abstract: A step detection device detects the distance and the direction to a road surface around a vehicle, using a distance sensor mounted on the vehicle, and sets a first step determination position and a second step determination position on the road surface. Then, the step detection device calculates the height changes of the road surfaces at the first step determination position and the second step determination position based on the distance and the direction to the road surface, and detects a step on the road surface based on one of the step determination positions, the gradient of the height change of the road surface at the one being larger.

Abstract: Device (100) comprises: a stereo image acquisition unit (101) for acquiring a standard image and a reference image for a stereo image; an image segmenting unit (102) for acquiring standard pixel data and reference pixel data from the stereo image; a phase correction unit (103) for carrying out for each of the pixel data a phase correction process making the values of the standard pixel data more symmetrical; a windowing unit (104) for applying a windowing function to each of the pixel data that have undergone phase correction; a phase correlation unit 105 for calculating a phase correlation value between the two pixel data that have undergone windowing; and a peak position detection unit (106) for calculating, on the basis of the phase correlation value, the parallax of a corresponding point of the reference image with respect to a standard point on the standard image.

Abstract: A disparity calculation apparatus for a stereo camera implements ranging of an object that includes consecutive similar patterns. In stereo matching, if a plurality of corresponding point candidates are present in a sum of absolute differences or similar evaluation value distribution for a target point, an evaluation value map is generated by superimposing an evaluation value distribution of a target point, for which a plurality of corresponding points are determined to be present, and an evaluation value distribution of each other target point present in a peripheral area of that target point. The shape of an object is represented in real space around a target point for which a plurality of corresponding points are determined to be present. The true distance of a railing that extends in a straight line is determined by extracting a line segment with the strongest linearity in the evaluation value map.

Abstract: Provided is a stereo image processing device, with which it is possible to compute disparity with high precision even for an object of a small image region size in a baseline length direction. With this device, an image matching unit (102) acquires a correspondence point of a reference image for a target point of a target image. An image cropping unit (201) extracts first two-dimensional pixel data including the target point from the target image, and extracts second two-dimensional pixel data including the correspondence point from the reference image. An image reconfiguration unit (202) reconfigures the respective first two-dimensional pixel data and second two-dimensional pixel data into first one-dimensional pixel data and second one-dimensional pixel data. A peak position detection unit (104) computes disparity based on the correlation between the first one-dimensional pixel data and the second one-dimensional pixel data.

Abstract: A stereo image processor (1) performs image matching, in an image matching section (6), on partial images of the same object included in a base image and a comparative image respectively and detects pixel-precision partial displacement between the base image and the comparative image based on a result of the image matching. Next, in an inverted phase filter processing section (9) in a second matching section (8), pixel values from the comparative image are filtered with an inverted phase filter using, as a filter coefficient, pixel values from the base image with the order thereof reversed, given the partial images of the same object that have minimum pixel-precision partial displacement. Then, in a peak detecting section (10), a peak position where an output value of the filtering with the inverted phase filter is maximum is detected and sub-pixel-precision partial displacement between the base image and the comparative image is detected based on the peak position.

Abstract: An image segmenting unit (401) in the stereo image processing device (100) extracts M (a natural number between 2 and N, inclusive) number of segmented target images wherein a first partial area within a target image has been segmented into N (a natural number of 2 or more), and also extracts M number of segmented reference images wherein a second partial area within a reference image has been segmented into N. An image concatenating unit (402) serially concatenates M data strings, each comprising a intensity value from each segmented target image, to form a first image data string and also serially concatenates M data strings, each comprising a intensity value from each segmented reference image, to form a second image data string. A filtering unit (403) and a peak position detection unit (104) calculate the disparity between the standard images and the reference images.

Abstract: Device (100) comprises: a stereo image acquisition unit (101) for acquiring a standard image and a reference image for a stereo image; an image segmenting unit (102) for acquiring standard pixel data and reference pixel data from the stereo image; a phase correction unit (103) for carrying out for each of the pixel data a phase correction process making the values of the standard pixel data more symmetrical; a windowing unit (104) for applying a windowing function to each of the pixel data that have undergone phase correction; a phase correlation unit 105 for calculating a phase correlation value between the two pixel data that have undergone windowing; and a peak position detection unit (106) for calculating, on the basis of the phase correlation value, the parallax of a corresponding point of the reference image with respect to a standard point on the standard image.

Abstract: Provided is a stereo image processing apparatus wherein parallax can be calculated with high precision. A window-function shifting unit (411) sets a third window function, which is formed by shifting a second window function on the basis of the amount of deviation in sub-pixel units, onto an image cutting-out unit (412). The image cutting-out unit (412) applies the second window function to a position subjected to a cut-out, cuts out a unit partial target image from a standard image, applies the second window function or the third window function, and cuts out a unit partial reference image from a reference image. A peak-position detection unit (106) calculates the amount of deviation in sub-pixel units on the basis of the phase difference between a data string comprising brightness of the cut-out unit partial target image, and a data string comprising brightness of the cut-out unit partial reference image.

Abstract: Provided is a stereo distance measurement apparatus wherein a camera image itself is adjusted to correct the blur, thereby preventing the distance measurement time from being long, while improving the precision of disparity detection. In the apparatus (100), a blur adjusting unit (102) uses a filter to tailor the blur of one of two images used by a disparity measuring unit (103), to the blur of the other which is weaker. A camera image itself is adjusted, whereby the blur can be corrected. Moreover, tailoring the blur of the one image to the blur of the other image which is weaker allows an application of the filter, which is a simple processing, to cause the blurs of the images used in the disparity detection, to coincide with each other. Therefore, the precision of disparity detection can be improved, while the distance measurement can be performed at a high speed.

Abstract: A stereo image processor (1) performs image matching, in an image matching section (6), on partial images of the same object included in a base image and a comparative image respectively and detects pixel-precision partial displacement between the base image and the comparative image based on a result of the image matching. Next, in an inverted phase filter processing section (9) in a second matching section (8), pixel values from the comparative image are filtered with an inverted phase filter using, as a filter coefficient, pixel values from the base image with the order thereof reversed, given the partial images of the same object that have minimum pixel-precision partial displacement. Then, in a peak detecting section (10), a peak position where an output value of the filtering with the inverted phase filter is maximum is detected and sub-pixel-precision partial displacement between the base image and the comparative image is detected based on the peak position.

Abstract: Provided is a stereo image processing device, with which it is possible to compute disparity with high precision even for an object of a small image region size in a baseline length direction. With this device, an image matching unit (102) acquires a correspondence point of a reference image for a target point of a target image. An image cropping unit (201) extracts first two-dimensional pixel data including the target point from the target image, and extracts second two-dimensional pixel data including the correspondence point from the reference image. An image reconfiguration unit (202) reconfigures the respective first two-dimensional pixel data and second two-dimensional pixel data into first one-dimensional pixel data and second one-dimensional pixel data. A peak position detection unit (104) computes disparity based on the correlation between the first one-dimensional pixel data and the second one-dimensional pixel data.

Abstract: A stereo image processor (1) performs image matching, in an image matching section (6), on partial images of the same object included in a base image and a comparative image respectively and detects pixel-precision partial displacement between the base image and the comparative image based on a result of the image matching. Next, in an inverted phase filter processing section (9) in a second matching section (8), pixel values from the comparative image are filtered with an inverted phase filter using, as a filter coefficient, pixel values from the base image with the order thereof reversed, given the partial images of the same object that have minimum pixel-precision partial displacement. Then, in a peak detecting section (10), a peak position where an output value of the filtering with the inverted phase filter is maximum is detected and sub-pixel-precision partial displacement between the base image and the comparative image is detected based on the peak position.

Abstract: Provided is a stereo image processing apparatus and a method of processing a stereo image, wherein calculation precision of disparity is improved, while maintaining a processing amount equal to the SAD method. In the stereo image processing apparatus (200), a data deletion unit (201) is installed in a stage prior to an image matching unit (102) and a filter unit (103), and forms a thinned-out target image and a thinned-out reference image, by thinning out a target image and a reference image. The filter unit (103) carries out filtering that uses an inverted phase filter, which is matching based on phase correlation.

Abstract: An object detection device that can accurately identify an object candidate in captured stereo images as an object or a road surface. The object detection device (100) have a disparity map generator (120) that generates a disparity map based on the stereo images; a road surface estimator (130) that estimates a road surface based on the disparity map; an object candidate location extractor (140) that extracts an object candidate region above the road surface, based on the disparity map and the road surface; an object identifying region extractor (150) that extracts an object identifying region including a region around the object candidate region; a geometric feature extractor (160) that extracts a geometric feature of the object candidate based on the object identifying region; and an object identifying unit (170) that identifies whether the object candidate is an object or a road surface based on the geometric feature.

Abstract: A disparity calculation apparatus for a stereo camera implements ranging of an object that includes consecutive similar patterns. In stereo matching, if a plurality of corresponding point candidates are present in a sum of absolute differences or similar evaluation value distribution for a target point, an evaluation value map is generated by superimposing an evaluation value distribution of a target point, for which a plurality of corresponding points are determined to be present, and an evaluation value distribution of each other target point present in a peripheral area of that target point. The shape of an object is represented in real space around a target point for which a plurality of corresponding points are determined to be present. The true distance of a railing that extends in a straight line is determined by extracting a line segment with the strongest linearity in the evaluation value map.