Abstract: In a travel road shape recognition apparatus, a first travel road shape, which approximates a shape of a road boundary, is calculated based on feature points indicating the travel road boundary in a captured image. A worsening position, which is a position on the calculated first travel road shape at which a degree of coincidence with the feature points worsens, is detected over an area from near to far from an own vehicle. A second travel road shape, which approximates a shape of the road boundary in an area farther from the own vehicle, beyond the worsening position, is calculated. The road boundary in the area nearer to the own vehicle, up to the worsening position, is recognized from the first travel road shape. The road boundary in the area farther from the own vehicle, beyond the worsening position, is recognized from the second travel road shape.

Abstract: A vehicle localization system is provided which localizes a system-equipped vehicle. The vehicle localization system determines a position of the system-equipped vehicle on a map using a map matching technique. The vehicle localization system also calculates a variation in arrangement of feature points (e.g., edge points) of a roadside object around the system-equipped vehicle in a captured image and corrects the calculated position of the system-equipped vehicle on the map using the variation in arrangement of the feature points. This ensures a required accuracy in localizing the system-equipped vehicle.

Abstract: A position identifying apparatus includes a position detecting unit; an information acquiring unit; a feature extracting unit; an index value calculating unit; a feature selecting unit; a correlating unit; a weight setting unit; and a correcting unit. The position detecting unit performs a map matching to detect a vehicle position on a map. The information acquiring unit acquires road information from the map. The feature extracting unit extracts features of ground object. The index value calculating unit calculates an index value representing a likelihood of a stationary object. The feature selecting unit selects feature candidates among the features having the index values larger than or equal to a predetermined likelihood of the stationary object. The correlating unit correlates the feature candidates with the road information. The weight setting unit sets weights of the feature candidates. The correcting unit corrects the position of the vehicle using the weights.

Abstract: An apparatus for recognizing lane partition lines on opposite sides of a traveling lane in a processing area of a forward image captured by a camera mounted in a vehicle. In the apparatus, a lane change determiner is configured to determine whether or not there is a lane change made by the vehicle. A processing area changer is configured to, while it is determined by the lane change determiner that there is a lane change, change the processing area from a predefined processing area to a processing area that can accommodate the lane change.

Abstract: A solid-state imaging device has a plurality of micro lenses, a first substrate, and a second substrate. The first substrate has a plurality of first photoelectric conversion units. Each of the plurality of first photoelectric conversion units corresponds to any one of the plurality of micro lenses. The second substrate has a plurality of second photoelectric conversion units and a plurality of third photoelectric conversion units. A plurality of pairs of photoelectric conversion units are disposed, and each of the plurality of pairs of photoelectric conversion units includes one of the second photoelectric conversion units and one of the third photoelectric conversion units. Each of the plurality of pairs of photoelectric conversion units corresponds to at least one of the plurality of first photoelectric conversion units. The second substrate further includes charge isolation regions disposed between the second photoelectric conversion units and the third photoelectric conversion units.

Abstract: Problem: To provide an optically clear adhesive with a high dielectric constant having an excellent balance of adhesive strength and cohesive strength as well as excellent optical characteristics, and an optical laminate containing the same. Solution: The optically clear adhesive of an embodiment of the present disclosure comprises a polymer of an acrylic monomer composition containing a hydroxyl group-containing monomer and at least 0.09 mass % and less than 50 mass % of a monofunctional alkyl (meth)acrylate, wherein the number of moles of OH in 100 g of the adhesive is at least 0.3 and at most 0.90.

Abstract: In an image processing apparatus, an image data acquisition unit acquires image data including R-pixels which are red pixels, holding red luminance values, B-pixels which are blue pixels, holding blue luminance values, G-pixels which are green pixels, holding green luminance values, and C-pixels which are clear pixels, holding luminance values in a wavelength range including wavelength ranges corresponding to red, blue and green. In the apparatus, a determination unit determines whether or not an inequality given by Valc?Valx<? is satisfied, where Valx is a luminance value of a pixel of interest that is one of the R-, B-, and G-pixels in the image data, Valc is a luminance value of the C-pixel or pixels closest to the pixel of interest, and ? is a constant, and if the inequality is satisfied, a correction unit corrects the luminance value Valx to be less than the luminance value Valc.

Abstract: Nanostructured material exhibiting a random anisotropic nanostructured surface, and exhibiting an average reflection at 60 degrees off angle less than 1 percent. The nanostructured materials are useful, for example, for optical and optoelectronic devices, displays, solar, light sensors, eye wear, camera lens, and glazing.

Abstract: As a data analysis apparatus that can easily and intuitively identify fine particles and small fine particle populations to be analyzed in a distribution graph and that can obtain accurate statistical data regarding these, a 3D data analysis apparatus is provided that includes a data storage unit which saves measurement data regarding fine particles, an input unit which selects independent three types of variables from the measurement data, a data processing unit which calculates positions and figures in a coordinate space whose coordinate axes are the three types of variables and which creates a 3D stereoscopic image representing characteristic distribution of the fine particles, and a display unit which displays the 3D stereoscopic image and that displays, in the 3D stereoscopic image, the figures in each region of the coordinate space divided into a plurality of regions by a plane in a different color in each region.

Abstract: In an example embodiment, may be embodied in a a data analysis apparatus comprises a control unit configured to provide data representative of a three dimensional image, the three dimensional image including at least a three dimensional coordinate space which includes at least one plane that divides the three dimensional coordinate space into at least two regions, a display unit configured to produce the three dimensional image based on the data representative of the three dimensional image, and an input unit configured to provide data representative of at least one of a movement and a position of the at least one plane. In other example embodiments, the present disclosure may be embodied in a data analysis server, a data analysis system, and/or a computer readable medium.

Abstract: An in-vehicle system as a road curvature detection device calculates a curvature of a road in front of a vehicle based on an acquired front scene image. The in-vehicle system receives gradient information from the data map. The gradient information corresponds to a current road section on the road on which the vehicle drives. The in-vehicle system detects a gradient accuracy of the received gradient information. When the current road section has a gradient, i.e. the road is an uphill or downhill road, the in-vehicle system selects an appropriate special detection methods based on the gradient accuracy of the received gradient information, and calculates a road curvature by using the selected special detection method. Each of the special detection methods calculates a road curvature while effectively suppressing influence of a road gradient indicated by the received gradient information.

Abstract: A travel lane marking probability calculating unit calculates a travel lane marking probability of each of travel lane marking candidates based on a calculation condition. A travel lane marking recognizing unit recognizes, as a travel lane marking, a travel lane marking candidate having a travel lane marking probability that is a threshold value or higher, among the travel lane marking candidates. A lane change detecting unit detects that an own vehicle is in the midst of a lane change. When the own vehicle is in the midst of a lane change, a condition changing unit changes the calculation condition to allow the travel lane marking probability to be more easily increased compared to when the own vehicle is not in the midst of a lane change, or changes the threshold value to be lower than that when the own vehicle is not in the midst of a lane change.

Abstract: This invention is provided with: a camera for capturing the image of a travel path; an edge point extraction unit for extracting edge points on the basis of the brightness of an image captured by the camera; a candidate line extraction unit for extracting, on the basis of the succession of the extracted edge points, a candidate line for a boundary line demarcating the travel path; a frequency calculation unit for calculating, on the basis of edge points belonging to the candidate line extracted by the candidate line extraction unit, the frequency distribution of the edge points for a parameter that specifies the width of the boundary line; a probability generation unit for calculating, on the basis of the frequency distribution calculated by the frequency calculation unit, the distribution for the probability that the candidate line at the parameter is the boundary line; and a boundary line recognition unit for recognizing the boundary line on the basis of the probability distribution calculated by the probab

Abstract: An on-board camera captures an image of a travel lane ahead of an own vehicle. At least one state acquisition apparatus acquires an acquired value indicating a state of the own vehicle. A travel lane marking recognition system recognizes a travel lane marking that demarcates the travel lane from an image captured by the on-board camera. The travel lane marking recognition system sets a reliability level of the recognized travel lane marking based on the acquired value of the at least one state acquisition apparatus. When the reliability level is higher than a first predetermined threshold, the travel lane marking recognition system performs driving control of the own vehicle based on the recognized travel lane marking. When the reliability level is lower than the first predetermined threshold, the travel lane marking recognition system performs a deviation warning of deviation from the travel lane based on the recognized travel lane marking.

Abstract: In a travel division line recognition apparatus, an extracting unit extracts a travel division line candidate from an image of a surrounding environment including a road, captured by an on-board camera. A calculating unit calculates a degree of reliability that the extracted travel division line candidate will be the travel division line. A recognizing unit selects the travel division line candidate based on the calculated degree of reliability, and recognizes the travel division line using the selected travel division line candidate. In the calculating unit, a solid object processing unit recognizes solid objects including vehicles, sets a suppression area including a frontal-face suppression area covering a frontal face of the other vehicle and a side-face suppression area covering a side face of the other vehicle, based on the recognized solid objects, and reduces the degree of reliability of the travel division line candidate present within the suppression area.

Abstract: Nanostructured material exhibiting a random anisotropic nanostructured surface, and exhibiting an average reflection at 60 degrees off angle less than 1 percent. The nanostructured materials are useful, for example, for optical and optoelectronic devices, displays, solar, light sensors, eye wear, camera lens, and glazing.

Abstract: An in-vehicle camera obtains image frames of a scene surrounding an own vehicle on a roadway. An extracting section in a lane boundary line recognition device extracts white line candidates from the image frames. The white line candidates indicate a degree of probability of white lines on an own vehicle lane on the roadway and a white line of a branch road which branches from the roadway. A branch judgment section calculates a likelihood of the white line as the white line of the branch road, and judges whether or not the white line candidate is the white line of the branch road based on the calculated likelihood. The branch judgment section decreases the calculated likelihood when a recognizable distance of the lane boundary line candidate monotonically decreases in a predetermined number of the image frames.

Abstract: In an apparatus for recognizing a location of an own vehicle, a detector is configured to detect one or more own-vehicle location candidates on roads based on map data. A partition line determiner is configured to, based on a captured image of a road around the own vehicle, determine a line type of each of partition lines extending along edges of the road. A determiner is configured to, for each of the one or more own-vehicle location candidates, under assumption that the own vehicle is at the own-vehicle location candidate, if the own vehicle is passing an intersection, determine, based on the line type of each of partition lines, a degree of confidence indicative of a likelihood that the own-vehicle location candidate at which it is assumed that the own vehicle is present is a location of the own vehicle.

Abstract: A traffic lane marking recognition apparatus includes a candidate detecting unit, a gap detecting unit, and a recognition reducing unit. The candidate detecting unit detects a lane dividing line candidate which is a candidate for a lane dividing line that defines a traffic lane on a road, based on an image of the road captured by an on-board camera that is mounted in a vehicle. The gap detecting unit detects a gap included in the lane dividing line candidate detected by the candidate detecting unit. When the gap is detected by the gap detecting unit, the recognition reducing unit reduces a probability of recognition of the lane dividing line candidate as a lane dividing line to a first probability that is lower than the probability when the gap detecting unit does not detect the gap, in a region from the gap closest to the vehicle towards a direction away from the vehicle.

Abstract: In vehicle-lane boundary line detection, low-luminance values are acquired from areas corresponding to below a tire and directly below a vehicle center based on a road surface image. A snow rut degree is calculated based on a luminance ration between the areas. A probability is calculated from a map based on the calculated snow rut degree. A parameter indicating the degree of snow rut likeness is calculated by a low-pass filtering process. A snow rut determination is made by the calculation result being compared with a predetermined threshold. A final determination of whether or not a snow rut is present is made, with reference to an outside temperature. When determined that a snow rut is present, a determination is made not to perform the detection. When determined that a snow rut is not present, a determination is made to perform the detection.