Microsoft Technology Licensing, LLC

The University of Tokyo

The Foundation for the Promotion of Industrial Science

Fujitsu Corporation

Other

Sony Corporation

Canon Kabushiki Kaisha

Japan Science and Technology Agency

Riken Corporation

Fujitsu Microelectronics Limited

Katsushi Ikeuchi

Masao Sakauchi

Shunsuke Kamijo

Johnny Hsienchow Lee

Ryo Ishikawa

Shuntaro Yamazaki

Masaaki Fukumoto

David William Baumert

Hideto Takeuchi

Hiroshi Kawasaki

Bo Zheng

Jordan Lee Kravitz

Zhengyou Zhang

Kiyohide Satoh

Kiwamu Kase

Tomohito Masuda

Ko Nishino

Ryusuke Sagawa

Taiki Fukiage

Mona Soliman Habib

Takeshi Oishi

Takeshi Ohishi

Kazuhide Hasegawa

Jun Takamatsu

Kazuhiro Sasabuchi

Naoki Wake

Yonggi Sun

Noise reduction in a robot system includes the use of a gesture library that pairs noise profiles with gestures that can be performed by the robot. A gesture to be performed by the robot is obtained, and the robot performs the gesture. The robot's performance of the gesture creates noise, and when a user speaks to the robot while the robot performs a gesture, incoming audio includes both user audio and robot noise. A noise profile associated with the gesture is retrieved from the gesture library and is applied to remove the robot noise from the incoming audio.

Noise reduction in robot human communication

Traditionally, robots may learn to perform tasks by observation in clean or sterile environments. However, robots are unable to accurately learn tasks by observation in real environments (e.g., cluttered, noisy, chaotic environments). Methods and systems are provided for teaching robots to learn tasks in real environments based on input (e.g., verbal or textual cues). In particular, a verbal-based Focus-of-Attention (FOA) model receives input, parses the input to recognize at least a task and a target object name. This information is used to spatio-temporally filter a demonstration of the task to allow the robot to focus on the target object and movements associated with the target object within a real environment. In this way, using the verbal-based FOA, a robot is able to recognize 'where and when' to pay attention to the demonstration of the task, thereby enabling the robot to learn the task by observation in a real environment.

Verbal-based focus-of-attention task model encoder

A method and apparatus for robot gesture generation is described. Generally speaking, a concept corresponding to a utterance to be spoken by a robot is determined (). After a concept is determined or selected, a symbolic representation of a gesture that corresponds to the determined concept is retrieved from a predetermined gesture library (). Subsequently, the symbolic representation is provided to cause the robot to perform the gesture (). In such way, a more natural, comprehensive and effective communication between human and robots may be achieved.

Robot gesture generation

Noise reduction in a robot system includes the use of a gesture library that pairs noise profiles with gestures performed by the robot. A gesture to be performed by the robot is obtained, and the robot performs the gesture. The robot's performance of the gesture creates noise, and when a user speaks to the robot while the robot performs a gesture, incoming audio includes both user audio and robot noise. A noise profile associated with the gesture is retrieved from the gesture library and is applied to remove the robot noise from the incoming audio.

An image processing device is equipped with an image input unit, an arithmetic operation unit, and an a value updating unit. The image input unit accepts a first input image and a second input image that a virtual image has been superimposed on the first input image at a first transmittance. The arithmetic operation unit calculates, by comparison between results of operations performed on a composite image obtained by adding values that the first input image and the second input image have been respectively multiplied by a second transmittance and a value that the second transmittance has been subtracted from 1 and on the first input image, a visibility value at the second transmittance. The &#x3b1; value updating unit updates the second transmittance with a comparison between the visibility value and a target value. The arithmetic operation unit uses the updated second transmittance to recalculated the visibility value.

Image processing device and image processing method

There is provided an image processing apparatus which calculates a feature value of an image. The apparatus comprises first obtaining means for obtaining an image; calculation means for calculating a set of numerical values formed from degrees of contributions of each of a plurality of order, wherein the degree of contributions of each order indicate contributions of monomials of the order for intensity values which are calculated using an approximation polynomial, and wherein the approximation polynomial provides a relationship between a pixel position of the image and an intensity value at the pixel position and is formed from a plurality of the monomials each having an order out of the plurality of orders; and first output means for outputting the set of the calculated numerical values as the feature value of the image.

Image processing apparatus, image processing method and program

A registration processing apparatus generates a polynomial to calculate a value corresponding to a distance from the surface of a target object in a first image, and acquires a plurality of position coordinates on the surface of the target object in a second image. Then the apparatus respectively calculates a value corresponding to the distance from the surface of the target object in the first image using the polynomial, for position coordinates obtained by coordinate conversion of the plurality of position coordinates. The apparatus coordinate-converts the position coordinates of the second image by a coordinate conversion method for the plurality of position coordinates determined based on the calculated values.

Registration processing apparatus, registration method, and storage medium

The present invention is a system for determining the three dimensional shape of an object, having a first measuring means for measuring a first distance and direction from a fixed first observation point to a first group of measurement points on an object, and a second measuring means for measuring a second distance and direction from a movable second observation point to a second group of measurement points on the aforementioned object, at least one point among said second group of measurement points being the same measurement point as at least one point among the aforementioned first group of measurement points, and said second group of measurement points including at least one measurement point not included in the aforementioned first group of measurement points, and further being provided with a calculating means for calculating the traveling velocity vector of the second observation point from the measurement results concerning the aforementioned same measurement point due to the first and second measuring means, correcting the aforementioned second measurement results based upon said traveling velocity vector, and calculating the three dimensional coordinates of the measurement points of the first group and the second group, and a displaying means that displays an image of the object based upon the aforementioned three dimensional coordinates.

Shape measurement device and method thereof

A feature amount of an inter-mobile unit relative movement are detected as an observation amount by an observation amount detecting section, time series of the observation amounts are stored as an observation series into a storage sectionto calculate a similarity of the observation series to a predetermined collision observation series by a classification section. A determination sectiondetermines to be a collision accident if, in a case where the similarity is larger than a predetermined value, a mobile unit associated with the similarity is at rest in a stoppage prohibition area set in a storage sectionand another mobile unit is moving, and to be a mobile unit failure if collision determination conditions except for the similarity are met. By consisting of not only a first scalar obtained by quantizing a relative velocity vector between mobile units but also a second scalar obtained by quantizing a relative position vector between mobile units as the observation amount, a relative movement between mobile units is classified in more detail. A mobile unit is tracked in units of block by a mobile unit tracking sectionto discriminate overlapped mobile units in pictures.

Method and apparatus for processing pictures of mobile object

This invention provides an apparatus and the like, which render an object from a predetermined view direction by a method using microfacet billboarding using 2D images obtained by photographing an object to be rendered from a plurality of photographing directions, and a depth image of the object to be rendered. This method obtains the geometrical shape of the object to be rendered on the basis of the depth image and the like, and approximates the geometrical shape using a set of microfacets whose directions change depending on the view direction. By mapping 2D images selected based on the view direction and photographing directions onto the respective microfacets as texture images, an arbitrary shaped object and landscape can be efficiently rendered.

Image processing apparatus, image processing method, and image processing program

An apparatus for generating an image includes a vehicle moving at a predetermined direction; and a plurality of cameras arranged on the vehicle along a linear line parallel to the predetermined direction and at different angles from each other with respect to the predetermined direction so as to include all areas of images to be acquired. The apparatus forms one image by integrating images at the same point acquired by the cameras, respectively without being synchronized the cameras with each other and using any external sensor.

Apparatus and method for generating image

By narrow region communication between a gate side communication apparatus (G-COM) and a mobile unit side communication apparatus (M-COM) passing through an on-road real gate at an interconnection, the G-COM assigns a real identification code (R-ID) IDincluding an intersection number to the M-COM after receiving a R-ID IDhaving been assigned from the M-COM, while time series pictures of the intersection including all real gates are taken by a camerainstalled to assign a virtual identification code (V-ID) to a mobile unit passing through a slit, corresponding to a real gate, in pictures by processing them. In response to the assignment of the R-ID, the R-ID is brought into correspondence with the V-ID. The mobile unit is tracked and when an anomalous behavior thereof is detected in pictures, warning information is transmitted to the M-COM using the corresponding R-ID. By gathering sets of IDand IDassociated with each other in a plurality of intersections, a mobile unit having displayed an anomalous behavior is tracked.

Mobile unit identification apparatus and method and apparatus for automatically warning to mobile unit

An implicit function field of a nonmanifold is held in a form of volume data; a value of an implicit function at a point between lattice points is decided by interpolation; and if a difference in code distances between two adjacent voxels to be interpolated is larger than a fixed width, no surface is formed between the voxels. Furthermore, an entered curved surface is broken down into curved surface patches which enable determination of a front and a back; numbers are given to the front and the back, respectively, to be distinguished from each other; and a space is classified into a plurality of regions by using the number of a surface of a nearest point.

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Yokohama, Japan

Katsushi Ikeuchi