Abstract: An object of the present invention is to provide a water level measurement device and a shoreline extraction method each of which is capable of stably measuring the water level. A pixel selection unit (11) selects a pixel of interest (302) from a designated area (301) designated from a captured image (300), and an identification image extraction unit (12) extracts identification images (303), (304) each coming in contact with the pixel of interest (302). The identification unit (13) calculates an identification strength indicating a degree to which an area corresponding to each of the identification images (303), (304) is a water area, on a basis of the result of machine learning related to identification between the water area and a non-water area.

Abstract: The navigation apparatus calculates second navigation parameters of a mobile object corresponding to data retrieved by a data retrieval unit by using a neural network that calculates first navigation parameters of the mobile object with the data used for calculating the first navigation parameters of the mobile object as an input.

Abstract: An attitude estimation apparatus (30) includes: a data acquiring unit (32) for acquiring observation data; a range-measurement point coordinate calculator (33A) for calculating geodetic coordinates of a range-measurement point in a geodetic coordinate system using positioning data, ranging data, actual attitude data, and an estimated value of an unknown parameter representing an attitude of a flying object; an image coordinate calculator (33B) for calculating coordinates of a projected point by performing projection transformation from the geodetic coordinate system to an image coordinate system on the geodetic coordinates; an image matching processor (34) for detecting image coordinates of the range-measurement point appearing in a first captured image by executing image matching between the first captured image and a second captured image selected from captured images; and an attitude estimator (35) for correcting the estimated value such that a magnitude of a difference between the coordinates of the proje

Abstract: An image feature map generating unit (3) generates, on the basis of feature amounts extracted from a plurality of images successively captured by a camera (109), an image feature map which is an estimated distribution of the object likelihood on each of the images. An object detecting unit (4) detects an object on the basis of the image feature map generated by the image feature map generating unit (3).

Abstract: A processor outputs laser irradiation location identifying pattern information for displaying a laser irradiation location identifying pattern from a laser measuring device to a display screen of a display. The processor receives reflection intensity value information including reflection intensity values of laser light, and determines a laser irradiation location on the display screen of the display on the basis of the reflection intensity values included in the reflection intensity value information, the reflection intensity value information being outputted from the laser measuring device having received the laser light emitted from the laser measuring device and reflected from the laser irradiation location identifying pattern displayed on the display screen of the display. The processor outputs camera calibration pattern information for displaying a camera calibration pattern on the display screen of the display.

Abstract: An object of the present invention is to provide a water level measurement device and a shoreline extraction method each of which is capable of stably measuring the water level. A pixel selection unit (11) selects a pixel of interest (302) from a designated area (301) designated from a captured image (300), and an identification image extraction unit (12) extracts identification images (303), (304) each coming in contact with the pixel of interest (302). The identification unit (13) calculates an identification strength indicating a degree to which an area corresponding to each of the identification images (303), (304) is a water area, on a basis of the result of machine learning related to identification between the water area and a non-water area.

Abstract: An object detection device includes: an optical flow calculator to calculate an optical flow between images captured by the image capturer at different times; an evaluation value calculator to divide the image captured by the image capturer into areas, and calculate, for each divided area, an evaluation value by using the optical flows of pixels belonging to the divided area, the evaluation value indicating a measure of a possibility that the divided area is an object area representing part or whole of the object to be detected; and an area determinator to determine an area in an image, in which the object to be detected exists, by comparing the evaluation value of each divided area calculated by the evaluation value calculator with a threshold value.

Abstract: The present invention is provided with: a coordinates calculation unit (161) that, on the basis of data related to distance measurement points (P) indicating the distance to and the angle of a respective plurality of distance measurement points (P) and the coordinates of a laser beam irradiation reference point, and on the basis of the attitude angle of an aircraft (2), calculates coordinates of each of the distance measurement points (P) on a corresponding image among a plurality of images; a feature point extraction unit (162) that extracts feature points for each of the images; a distance calculation unit (163) that calculates, for each of the distance measurement points (P), the distance to a nearby feature point among the feature points extracted by the feature point extraction unit (162) on the basis of the coordinates calculated in the corresponding image by the coordinates calculation unit (161); and a necessity determination unit (166) that deletes unnecessary data from the data related to the distan

Abstract: An attitude estimation apparatus (30) includes: a data acquiring unit (32) for acquiring observation data; a range-measurement point coordinate calculator (33A) for calculating geodetic coordinates of a range-measurement point in a geodetic coordinate system using positioning data, ranging data, actual attitude data, and an estimated value of an unknown parameter representing an attitude of a flying object; an image coordinate calculator (33B) for calculating coordinates of a projected point by performing projection transformation from the geodetic coordinate system to an image coordinate system on the geodetic coordinates; an image matching processor (34) for detecting image coordinates of the range-measurement point appearing in a first captured image by executing image matching between the first captured image and a second captured image selected from captured images; and an attitude estimator (35) for correcting the estimated value such that a magnitude of a difference between the coordinates of the proje

Abstract: An information processing unit (32) collects accident information from a vehicle-mounted device (2) existing in a periphery of a site of an accident indicated by accident information stored in a storage unit (31), by controlling a communication unit (30).

Abstract: A return point acquiring unit refers to both a first optical flow from an image to an image, and a second optical flow from the image to the image, to acquire the coordinates of a return point which is an end point of the second optical flow. An accuracy calculating unit calculates the accuracy of the optical flows on the basis of the difference between the coordinates of a start point of the first optical flow and the coordinates of the return point acquired by the return point acquiring unit.

Abstract: An image feature map generating unit (3) generates, on the basis of feature amounts extracted from a plurality of images successively captured by a camera (109), an image feature map which is an estimated distribution of the object likelihood on each of the images. An object detecting unit (4) detects an object on the basis of the image feature map generated by the image feature map generating unit (3).

Abstract: Image matching on a pair of image data about images which are shot at different shooting positions is performed, and a point corresponding to the coordinates of a distance measurement point on the image shown by one image data of the pair is searched through the image shown by the other image data of the pair. The value of a parameter showing the attitude of an airplane (2) is corrected in such a way that the difference between the coordinates of the distance measurement point on the image shown by the other image data of the pair and the coordinates of the corresponding point which is searched for via the image matching becomes small, to estimate the attitude of the airplane (2).

Abstract: An object detection device includes: an optical flow calculator to calculate an optical flow between images captured by the image capturer at different times; an evaluation value calculator to divide the image captured by the image capturer into areas, and calculate, for each divided area, an evaluation value by using the optical flows of pixels belonging to the divided area, the evaluation value indicating a measure of a possibility that the divided area is an object area representing part or whole of the object to be detected; and an area determinator to determine an area in an image, in which the object to be detected exists, by comparing the evaluation value of each divided area calculated by the evaluation value calculator with a threshold value.

Abstract: Image matching on a pair of image data about images which are shot at different shooting positions is performed, and a point corresponding to the coordinates of a distance measurement point on the image shown by one image data of the pair is searched through the image shown by the other image data of the pair. The value of a parameter showing the attitude of an airplane (2) is corrected in such a way that the difference between the coordinates of the distance measurement point on the image shown by the other image data of the pair and the coordinates of the corresponding point which is searched for via the image matching becomes small, to estimate the attitude of the airplane (2).

Abstract: It is an object to obtain a high-resolution image generation apparatus that can generate a high-quality image by sorting out good portions from faulty portions in optical flow. The present invention includes: a hard disk that stores multi-viewpoint image information and parameter information of a base image and a plurality of reference images; an optical flow computation unit that extracts a plurality of pairs of the base image and a reference image, the plurality of pairs each including a different reference image, and computes optical flow for each pair; a depth information computation unit that computes depth information which indicates depth of each pixel of the base image for each pair, based on optical flow and the parameter information; and an optical flow sorting unit that determines whether or not each piece of pixel-based correspondence information included in the optical flow of each pair is to be used for improving a resolution of the base image, based on two pieces of the depth information.

Abstract: It is an object to obtain a high-resolution image generation apparatus that can generate a high-quality image by sorting out good portions from faulty portions in optical flow. The present invention includes: a hard disk that stores multi-viewpoint image information and parameter information of a base image and a plurality of reference images; an optical flow computation unit that extracts a plurality of pairs of the base image and a reference image, the plurality of pairs each including a different reference image, and computes optical flow for each pair; a depth information computation unit that computes depth information which indicates depth of each pixel of the base image for each pair, based on optical flow and the parameter information; and an optical flow sorting unit that determines whether or not each piece of pixel-based correspondence information included in the optical flow of each pair is to be used for improving a resolution of the base image, based on two pieces of the depth information.

Abstract: An image generation system which comprises an image generation apparatus having viewpoint definition means for defining a virtual viewpoint placed in virtual three dimensions, virtual panel definition means for defining a virtual object displayed in the virtual three dimensions and defining a virtual panel being placed in the virtual three dimensions, the virtual panel onto which a moving image is projected, based on the virtual viewpoint and the virtual object, moving image selection means for selecting a moving image to be projected onto the virtual panel from among a plurality of moving images based on the virtual viewpoint defined in the viewpoint definition means, and virtual three-dimensional image generation means for placing the virtual panel defined in the virtual panel definition means in the virtual three dimensions, projecting the moving image selected by the moving image selection means onto the virtual panel, and generating an image from the virtual viewpoint defined in the viewpoint definition

Abstract: A drawing recognition system is disclosed which recognizes even a complex low-quality drawing containing overlapping charts, or many blurs or discontinuations with less operations. The system includes both a program for approximating a graphical object to be recognized and a program for approximating positions on the approximated graphical object. The system further includes a means for creating a chart model according to the designation, and a chart recognition means for matching the chart model and the chart to be recognized in the drawing.