Sony Corporation

Mitsubishi Chemical Corporation

Konica Minolta Business Technologies, Inc.

Mitsubishi Kasei Corporation

Asahi Kogaku Kogyo Kabushiki Kaisha

Konica Corporation

Hitachi, Ltd.

Oki Electric Industry Co., Ltd.

Sony Group Corporation

Mitsubishi Chemical Industries Limited

Konica Medical and Graphic Corporation

Pentax Corporation

Konica Minolta Medical and Graphic, Inc.

Noriaki Takahashi

Takahiro Nagano

Tetsujiro Kondo

Yasuhiro Suto

Osamu Ando

Hisakazu Shiraki

Satoshi Takami

Takashi Nakamura

Hitoshi Ono

Tameichi Ochiai

Tsutomu Watanabe

Takaaki Suzuki

Daisuke Ueda

Hideki Nagasaka

Masako Takeuchi

Takanori Kanda

Yuqing Xu

Hideaki Odagiri

Tomoko Ishikawa

Takanobu Ohba

Haruka Mitsumori

Yuto Kobayashi

Tomohiro Yamazaki

Hirokazu Matsumoto

Konoe Miura

Masahiro Nukui

Ryuichiro Takasaki

Hideko Akai

Haruka Asai

Kazunori Maruyama

Shinji Hamada

Takashi Kokubo

Takao Inoue

Takashi Sawao

Koji Yano

Masahiro Kaneko

Masato Hara

Kohei Iketani

Takeshi Miyai

Yasuo Oguri

Toshinobu Sugiyama

Takahiro Yokoyama

Tsunehiko Baba

Hiromasa Naganuma

Akihiro Okumura

Shigeru Okazaki

Makoto Ui

Tsutomu Ichikawa

Tomohiro Hanai

Katsuhisa Shinmei

Shigeki Shimizu

Eiichi Ito

Koji Takeshita

Masakazu Ando

Yukio Chida

Yasuhiro Kameyama

Satoru Watanabe

Yuki Tokizaki

Keisuke Chida

Hiroshi Ide

Hiroto Itoh

Teruo Sakai

Kazuo Mitsuhashi

Akinobu Oshima

Usei Jo

Akihiko Yanagibori

Kazuhiro Yamazaki

Katsuo Koizumi

Noriko Watanabe

Takayuki Kanai

Tomoyo Ishiguro

Hirofumi Oda

Yuji Uyama

Takashi Ichimura

An information processing apparatus includes a cost evaluation unit and a correction processing unit. The cost evaluation unit evaluates a correction residual after crosstalk correction processing as a cost. The correction processing unit performs a plurality of different pieces of crosstalk correction processing while determining a correction range and a correction amount based on the cost.

Information processing apparatus and information processing method

An artifact upon imaging degrades sensing accuracy of a projection image. An information processing device that develops a captured image thus performs interpolation processing using interpolation direction information according to a test pattern projected by a projection device. In other words, the interpolation processing of pixel information in an interpolation direction according to the obtained interpolation direction information is performed with respect to an image signal obtained by capturing the projection image of the test pattern. This can suppress the artifact and improve the sensing accuracy.

Information processing device, information processing method, and program

An information processing apparatus () includes: a specification unit () that specifies a viewpoint position of an observer of a display device () that reproduces rays of light that have been sent out by a three-dimensional object; a setting unit () that sets a region that makes it possible for the observer to stereoscopically view the three-dimensional object, by using, as a reference, the viewpoint position that has been specified by the specification unit (); and a display control unit () that performs control to cause the display device () to emit a ray-of-light group that makes it possible to stereoscopically view the three-dimensional object from an inside of the region that has been set by the setting unit (), and makes it impossible to stereoscopically view the three-dimensional object from an outside of the region.

Information processing apparatus, information processing method, and program

The present disclosure relates to an image processing apparatus and method that enable suppression of a reduction in subjective image quality. Image processing is performed on each of a plurality of frame images before projection. The image processing suppresses an influence of superimposition of the plurality of frame images in a projection image in projecting each of the plurality of frame images cyclically using a corresponding one of a plurality of projection sections. The plurality of frame images is included in a moving image. The present disclosure can be applied to, for example, an image processing apparatus, an image projection apparatus, a control apparatus, an information processing apparatus, an image projection system, an image processing method, a program, or the like.

Image processing apparatus and method

Correction performance is improved regarding a synthetic blur in which a plurality of blur characteristics is synthesized, for example, a focus blur that occurs in a superimposed projection image, or the like. An image processing device according to the present technology includes: a correction unit that obtains a plurality of blur-corrected images by performing blur correction processing on an input image regarding a focus blur that occurs in a projection image by an image projection device, by using a filter coefficient for blur correction corresponding to each of a plurality of blur characteristics, the filter each being obtained on the basis of the plurality of blur characteristics; and an image output unit that individually outputs the plurality of blur-corrected images obtained by the correction unit.

Image processing device and image processing method

The present technology relates to an image processing apparatus, an image processing method, and a program that allow an improvement in measurement accuracy by taking into account degradation occurring during projection and degradation occurring during imaging. An image processing apparatus according to an aspect of the present technology performs, on a test pattern image representing a predetermined test pattern, correction according to an imaging degradation model obtained by modeling degradation occurring during capturing of the test pattern image projected on a screen, and correction according to a projection degradation model obtained by modeling degradation occurring during projection of the test pattern image. The present technology can be applied to an image processing apparatus that controls projection by a projector.

Image processing apparatus, image processing method, and program

There is provided an image processing device, an image projection device, a control device, an information processing device, an image projection system, an image processing method, and a program that make it possible to suppress a reduction in a subjective image quality. On the basis of each frame image of a moving image, a time during which a projection image of each frame image of the moving image is viewable by a user is controlled. For example, a controller controls the time during which the projection image is viewable by the user, to cause a difference between the moving image and the projection image due to a reduction in a luminance and a difference between the moving image and the projection image, which increases due to an increase in the time during which the projection image is viewable by the user, to be suppressed.

Image processing device and method for suppressing a reduction in image quality

A search is enabled for an adjustment value with which a good blur correction effect is obtained by blur correction processing as an optical adjustment value of an image projection device, and blur correction performance is improved in a case where correction of a focus blur that occurs in a projection image is performed by signal processing. An image processing device according to the present technology includes: a blur correction unit that performs blur correction processing for focus blur correction on an input image on the basis of a blur characteristic that is a characteristic of a focus blur that occurs in a projection image of an image projection device, the blur characteristic being measured in a state where a predetermined candidate value is set as an optical adjustment value of the image projection device; and a use determination unit that performs evaluation regarding the focus blur on a projection image obtained by causing the image projection device to project an image subjected to the blur correction processing, and performs determination regarding whether or not the candidate value is usable on the basis of a result of the evaluation.

Provided is a computation method for obtaining information suitable for positional deviation correction and lens blur correction for a case where a part of or an entire projection image projected by each of a plurality of projectors is displayed in a superimposed manner. For this purpose, a light intensity distribution indicating a degree of lens blur of a base projector and peak coordinates of the light intensity distribution are calculated using a captured image obtained by capturing a test pattern projected by the base projector in an arrangement state in which a plurality of projectors is arranged such that a part of or an entire projection image projected by each of the plurality of projectors is displayed in a superimposed manner. Further, a light intensity distribution centered on the peak coordinates on the base projector side and corresponding to a degree of lens blur of a referencing projector is calculated using a captured image obtained by capturing the test pattern projected by the referencing projector in the same arrangement state. As a result, information indicating the degree of lens blur of the base projector and information corresponding to positional deviation and the degree of lens blur of the referencing projector are obtained.

Information processing apparatus, computation method of information processing apparatus, and program

Proposed is an evidence gathering system and method capable of reducing the burden on an operative performing system tests. A first agent which is installed in a client gathers evidence of a test result in the client at the time of a system test, and a second agent which is installed in a second server apparatus gathers evidence, of a test result in the second server apparatus at the time of the system test, which includes at least pre/post-update data of the database which has been updated as a result of the system test, gathers the evidence in the client of the system test from the first agent, gathers the evidence in the second server apparatus of the system test from the second agent, and integrates the gathered evidence for each of the system tests.

Evidence gathering system and method

A first-color-space converting unitreceives the image signal of first color space from a signal processing unitand converts the received image signal into the image signal of second color space which is suitable for conversion into the image signal of third color space as specified. A thinning processing unitperforms thinning process on the converted image signal representing each color component of the second color space for each pixel so as to correspond to a processor unitwhich generates the image signal representing each color component from the image signal representing one color component of color space for each pixel and output the image signal of the third color space, thereby turning it into the image signal representing one color component of the second color space for each pixel. It is possible to prevent the deterioration or the like of the image quality when the image signal representing one color component of the second color space for each pixel is output from an image pickup elementand processed by the processor unit

Image processing apparatus and image processing method, and image pickup element and image pickup apparatus

A coefficient learning apparatus includes a regression coefficient calculation unit configured to obtain a tap from an image of a first signal; a regression prediction value calculation unit configured to perform a regression prediction computation; a discrimination information assigning unit configured to assign discrimination information to the pixel of interest; a discrimination coefficient calculation unit configured to obtain a tap from the image of the first signal; a discrimination prediction value calculation unit configured to perform a discrimination prediction computation; and a classification unit configured to classify each of the pixels of the image of the first signal into one of the first discrimination class and the second discrimination class. The regression coefficient calculation unit further calculates the regression coefficient using only the pixels classified as the first discrimination class and further calculates the regression coefficient using only the pixel classified as the second discrimination class.

Coefficient learning apparatus and method, image processing apparatus and method, program, and recording medium

An image processing apparatus includes a storage unit in which regression coefficient data is stored for each class on the basis of a tap in which a linear feature amount corresponding to a pixel of interest of first image data and a non-linear feature amount determined from the image data are used as elements; a classification unit configured to classify each of linear feature amounts of a plurality of items of input data of the input first image into a predetermined class; a reading unit configured to read the regression coefficient data; and a data generation unit configured to generate data of a second image obtained by making the first image have higher quality by performing a product-sum computation process by using the regression coefficient data read from the reading unit and elements of the tap of each of the plurality of items of input data of the input first image.

Image processing apparatus and coefficient learning apparatus

A coefficient learning apparatus includes: a student-image generation section configured to generate a student image from the teacher image; a class classification section configured to sequentially set each of pixels in the teacher image as a pixel of interest and generate a class for the pixel of interest from the values of a plurality of specific pixels; a weight computation section configured to add up feature quantities; and a processing-coefficient generation section configured to generate a prediction coefficient on the basis of a determinant including said deterioration equation and a weighted constraint condition equation.

Learning of coefficients for motion deblurring by pixel classification and constraint condition weight computation

Provided is a failure recovery method for switching to a standby system if a failure occurs in an active system, which allows reduction of loads on the standby system and a network. A computer system, which receives data to which timestamp information is appended in a chronological order and processes the received data by registered queries, includes the active system for processing the received data and the standby system for processing the received data instead of the active system upon occurrence of a failure. The active system processes the received data by the respective queries according to a predefined sequence, and transmits results obtained from the received data by the respective queries to the standby system as intermediate data on a query basis at a predetermined timing. The standby system restores the data by processing the received data and the intermediate data if a failure occurs in the active system.

Failure recovery method, computer system, and storage medium recorded failure recovery program for a stream data processing system

Growing community of inventors

Tokyo, Japan

Noriaki Takahashi