Canon Kabushiki Kaisha

Honda Motor Co., Ltd.

Yasuhiro Okuno

Tadashi Yamakawa

Masaaki Nagashima

Takayuki Sasaki

Yasutomo Suzuki

Mamoru Sato

Hideo Noro

Taichi Matsui

Kazuyuki Fukamachi

Hirokazu Ohi

Kazumori Sakai

Michiaki Okubo

Kenji Morita

Katsuhiko Mori

Yusuke Mitarai

Takahiro Kurosawa

Shunta Tate

Sukeyuki Shinotsuka

Yosuke Tanaka

Kenichiro Kurai

Shoji Matsuda

Daiki Kurei

Shunsuke Torigai

Masakazu Matsugu

Akihiro Katayama

Hiroto Yoshii

Yasuhiro Komori

Toshikazu Ohshima

Kazuki Takemoto

Shingo Ito

Yasuo Katano

Tsuyoshi Kuroki

Sonoko Maeda

Kaname Tanimura

Kohei Seino

Yu Kurokawa

Genesio Agostinho Gomes Chang

Kazuya Kanekasu

Koki Isobe

Kotaro Nakamoto

Ryusei Homma

Kenichiro ' Kurai

Yu Tanabe

Disclosed are a see-through image display system and method. The see-through image display system includes: an image capturing device for photographer, configured to capture a photographer; a plurality of image capturing devices for object to be captured, configured to capture a target object to be captured; a viewing angle detection portion, configured to detect a viewing angle of the photographer according to an image of the photographer captured by the image capturing device for photographer; an image connection portion, configured to connect an overlapping portion of the images of object to be captured that are captured by the image capturing devices for object to be captured, so as to connect the images; an image generating portion, configured to perform homograph transformation on the images of object to be captured that are connected by the image connection portion based on the viewing angle of the photographer to generate a see-through image.

See-through image display system and method

An inspection device and an inspection method are provided. The inspection device includes: a main body portion, configured to be held by an inspector; a camera portion, disposed on the main body portion and configured to capture an inspected portion of a vehicle; and a guiding portion, configured to guide a camera direction of the camera portion to the inspector, so that an image obtained through the camera portion becomes a prescribed image suitable for inspection.

Inspection device and inspection method

An apparatus acquires a low-noise image, which is training data for training an image processing model, and a plurality of high-noise images corresponding to the same scene in the low-noise image data and each having different noise patterns. The apparatus calculates each of errors between a plurality of estimated output values, which is acquired by inputting a different one of the plurality of high-noise images to the image processing model and the low-noise image. Then, the apparatus calculates an anti-noise stability based on an error between the plurality of estimated output values, and trains the image processing model using a loss function including the errors between the plurality of estimated output values and the low-noise image and the anti-noise stability.

Apparatus, method, and storage medium

An information processing apparatus mounted to transport equipment includes a processor that downloads a program of the information processing apparatus by a wireless communication, in which the information processing apparatus has communication modes including a first communication mode in which a wireless communication unit connects to a neighboring wireless access point and performs a communication and a second communication mode in which the wireless communication unit functions as a wireless access point for neighboring radio equipment, and, the processor performs a switching from the second communication mode to the first communication mode and searches for the neighboring wireless access point based on the first communication mode to attempt to connect to the neighboring wireless access point if the processor executes, when a power source of the transport equipment turns off, a discrimination of the communication mode and discriminates that the communication mode is the second communication mode.

Information processing apparatus, transport equipment, information processing method, and computer-readable storage medium

A control system includes a management unit configured to control a power supply device toward a target value for an output performance value of the power supply device that supplies power to a predetermined device, and an acquisition unit configured to acquire information related to a post-shutdown task scheduled to be executed after a shutdown condition of the predetermined device is satisfied, in which the management unit refers to the information acquired by the acquisition unit, and, when the post-shutdown task is scheduled to be executed, sets the target value to a second target value which is higher than a first target value set when the post-shutdown task is scheduled to be executed, before the shutdown condition is satisfied.

Control system, control method, and program

A sensor axis adjustment method includes: a conveying process of disposing the vehicle V at a vehicle inspection position that is determined in an inspection chamber Rb; a first aiming process of disposing a first target robot Tat a first inspection position that is determined with respect to the first radar device R, and adjusting the optical axis of the first radar device R; and a second aiming process of disposing a second target robot Tat a second inspection position that is determined with respect to the second radar device R, and adjusting the optical axis of the second radar device R. An execution period of the first aiming process and an execution period of the second aiming process at least partially overlap each other.

Sensor axis adjustment method

The optical axis adjustment systemadjusts an optical axis O of a radar device R in a vehicle V in which the radar device R that detects an external environment is attached to a vehicle body B, and includes an adjustment target T that is movable in an inspection chamber Rb in which the vehicle body B is disposed, a radar attachment position and direction calculation unit that calculates an attachment position of the radar device R and a direction of the optical axis, a normal posture calculation unit that calculates a normal posture of the adjustment target T on the basis of a calculation result of the radar attachment position and direction calculation unit, and a target movement unit that sets a posture of the adjustment target T to a normal posture.

Sensor axis adjustment device and sensor axis adjustment method

The vehicle inspection device is used to adjust an optical axis of a radar device R in a vehicle in which the radar device R that acquires external environment information is attached to a vehicle body. The vehicle inspection device includes: a target robot T including a corner reflectorthat reflects an electromagnetic wave emitted from the radar device R, and an electromagnetic wave characteristic measurement devicethat measures characteristics of the electromagnetic wave emitted from the radar device R; and a control devicethat controls the target robot T. The control devicecalculates an attachment position of the radar device R and a direction of an optical axis on the basis of electromagnetic wave characteristics measured by the electromagnetic wave characteristic measurement device, and moves the target robot T to an inspection position that is determined on the basis of the calculation result.

Vehicle inspection device

An information processing apparatus includes a learning unit configured to learn a plurality of multi-layer neural networks configured to carry out a plurality of tasks, a generation unit configured to generate a shared layer candidate at a predetermined layer between or among the plurality of multi-layer neural networks, a first relearning unit configured to relearn the plurality of multi-layer neural networks in a structure using the shared layer candidate, and a determination unit configured to determine whether to share the shared layer candidate at the predetermined layer with respect to each of the plurality of tasks based on an evaluation of the relearning.

Information processing apparatus using multi-layer neural network and method therefor

An information processing apparatus includes a storing unit that stores a neural network that recognizes a data characteristic of data, and a correction unit that corrects the data by using the neural network stored in the storing unit such that the neural network recognizes that the data characteristic of the data is a predetermined data characteristic.

Information processing apparatus, information processing method, and storage medium

An information processing apparatus encodes an input pattern to a code including a plurality of bits, calculates reliabilities for respective bits of the code, generates a similar codes each similar to the code based on the reliabilities, and recognizes the input pattern based on the code and the similar codes.

Information processing apparatus and information processing method

An information processing apparatus sets a plurality of reference locations of data in information as one reference location pattern and acquires a feature amount obtained from a value of data of one of the plurality of pieces of reference information in one reference location pattern for each of a plurality of reference location patterns and the plurality of pieces of reference information. The apparatus extracts data included in the input information according to each of the plurality of reference location patterns, selects the reference location pattern for classification of the input information from the plurality of reference location patterns based on a value of data included in the extracted input information, and executes classification of the input information by using the feature amount in the selected reference location pattern and data included in the input information at a reference location indicated by the reference location pattern.

Information processing apparatus, information processing method and storage medium

Position and orientation information of a specific part of an observer is acquired (S). It is determined whether or not a region of a specific part virtual object that simulates the specific part and that of another virtual object overlap each other on an image of a virtual space after the specific part virtual object is laid out based on the position and orientation information on the virtual space on which one or more virtual objects are laid out (S). When it is determined that the regions overlap each other, an image of the virtual space on which the other virtual object and the specific part virtual object are laid out is generated; when it is determined that the regions do not overlap each other, an image of the virtual space on which only the other virtual object is laid out is generated (S).

Image processing apparatus and image processing method

An end user is provided with an environment to easily remote-control a video camera via a general network such as the Internet. For this purpose, on a client side, the content of camera control is described in file-transfer protocol description, and the description is transferred to a camera server on the Internet via a browser. The camera server interprets the description, controls a camera in accordance with the designated content, to perform image sensing, and returns the obtained video image as the content of a file to the client. The client performs various controls while observing the video image. When a desired angle has been found, the client instructs to register the angle in a bookmark, then angle information displayed at that time is registered. Thereafter, when the user of the client can see the video image obtained on the same image-sensing conditions by merely select-designating the angle information registered in the bookmark.

Communication method and apparatus, server and client on network, and program codes realizing communication thereof

An information processing apparatus that discriminates the orientation of a target includes a calculation unit that calculates a distribution of a difference in feature amount between a plurality of learning patterns each showing the orientation of a target, a determination unit that determines, using a probability distribution obtained from the distribution of differences calculated by the calculation unit, a pixel that is in an input pattern and is to be referred to in order to discriminate the orientation of a target in the input pattern, and a discrimination unit that performs discrimination for obtaining the orientation of the target in the input pattern by comparing a feature amount of the pixel determined by the determination unit and a threshold set in advance.

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Tokyo, Japan

Yasuhiro Okuno