Abstract: A recognition apparatus is provided which includes an input section that receives image information from a front camera and a rear camera, and a calculation section that performs a forward recognition process that is a recognition process targeting the image information from the front camera received by the input section and a rearward recognition process that is a recognition process targeting the image information from the rear camera received by the input section. The calculation section includes an acquisition section that acquires first information representing whether an own vehicle is in a state of moving forward or a state of moving rearward and second information representing a traveling condition of the own vehicle, and a process selection section that selects processes to be performed as the forward recognition process and the rearward recognition process, based on the first and second information acquired by the acquisition section.

Abstract: In an occupant detection system for detecting an occupant of a vehicle, an imaging unit captures an image of an interior of the vehicle and a lighting unit illuminates a region in a field of view of the imaging unit. A lighting control unit automatically controls the lighting unit so that an integrated amount of light of the lighting unit changes. An occupant detection unit detects an occupant based on the image captured by the imaging unit.

Abstract: A recognition apparatus is provided which includes an input section that receives image information from a front camera and a rear camera, and a calculation section that performs a forward recognition process that is a recognition process targeting the image information from the front camera received by the input section and a rearward recognition process that is a recognition process targeting the image information from the rear camera received by the input section. The calculation section includes an acquisition section that acquires first information representing whether an own vehicle is in a state of moving forward or a state of moving rearward and second information representing a traveling condition of the own vehicle, and a process selection section that selects processes to be performed as the forward recognition process and the rearward recognition process, based on the first and second information acquired by the acquisition section.

Abstract: In a shape measuring apparatus, an image processing unit derives, based on a calculated disparity, absolute distance information about a first imaging target located in a common image region from a shape measuring apparatus. The image processing unit reconstructs a 3D shape of each of imaging subjects including the first and second imaging subjects based on the sequential monochrome images.

Abstract: A vehicle detection apparatus detects an object based on an image captured from a vehicle. In the vehicle detection apparatus, a camera is mounted in the vehicle. A search region determining unit determines a region including a road surface in the image to be a search region. A cost minimizing unit divides the search region into two, an upper region and a lower region, by a boundary line, determines corresponding points in a plurality of images captured by the camera at different time points by applying an optical flow model having a fixed magnification factor to the upper region and an optical flow model having a planar constraint condition to the lower region, and determines a boundary line that minimizes cost related to a difference between pixel values of the corresponding points. A vehicle presence determining unit determines presence of a forward vehicle based on the boundary line.

Abstract: In a learning system, a storage stores training data. At least one processor performs a plurality of processes. Each of the processes calculates, based on the at least one parameter at a present time and the training data, a differential value for updating the at least one parameter in accordance with backpropagation. Each of the processes calculates, based on the differential value and the at least one parameter at the present time, a transmission value to be transmitted to the other processes. Each of the processes updates, based on the transmission values transmitted from the other processes, the at least one parameter at the present time.

Abstract: A detection device has a neural network process section performing a neural network process using parameters to calculate and output a classification result and a regression result of each of frames in an input image. The classification result shows a presence of a person in the input image. The regression result shows a position of the person in the input image. The parameters are determined based on a learning process using a plurality of positive samples and negative samples. The positive samples have segments of a sample image containing at least a part of the person and a true value of the position of the person in the sample image. The negative samples have segments of the sample image containing no person.

Abstract: A vehicle detection apparatus detects an object based on an image captured from a vehicle. In the vehicle detection apparatus, a camera is mounted in the vehicle. A search region determining unit determines a region including a road surface in the image to be a search region. A cost minimizing unit divides the search region into two, an upper region and a lower region, by a boundary line, determines corresponding points in a plurality of images captured by the camera at different time points by applying an optical flow model having a fixed magnification factor to the upper region and an optical flow model having a planar constraint condition to the lower region, and determines a boundary line that minimizes cost related to a difference between pixel values of the corresponding points. A vehicle presence determining unit determines presence of a forward vehicle based on the boundary line.

Abstract: A detection device has a neural network process section performing a neural network process using parameters to calculate and output a classification result and a regression result of each of frames in an input image. The classification result shows a presence of a person in the input image. The regression result shows a position of the person in the input image. The parameters are determined based on a learning process using a plurality of positive samples and negative samples. The positive samples have segments of a sample image containing at least a part of the person and a true value of the position of the person in the sample image. The negative samples have segments of the sample image containing no person.

Abstract: A sign recognition apparatus is mounted to an own vehicle. An on-board imaging device is mounted to the own vehicle and captures an image of a periphery of the own vehicle. The sign recognition apparatus recognizes traffic signs including a no-passing sign from the image of the periphery of the own vehicle that has been captured by the on-board imaging device. Based on predetermined features of the no-passing sign included in the recognized traffic signs, the sign recognition apparatus determines a left- or right-hand traffic division used in an area in which the no-passing sign is set and a distance unit used in the traffic signs.