Sony Computer Entertainment Inc.

Sony Corporation

Sony Interactive Entertainment Inc.

Other

Kabushiki Kaisha Toshiba

Sony Corporation Entertainment Inc.

Sne Platform Inc.

Akio Ohba

Hiroyuki Segawa

Tetsugo Inada

Hidehiko Ogasawara

Tomokazu Kake

Hirofumi Okamoto

Masaaki Oka

Nobuo Sasaki

Akihiko Sugawara

Akira Suzuki

Masakazu Suzuoki

Katsu Saito

Atsushi Kimura

Teiyu Goto

Shuji Hiramatsu

Shigeru Enomoto

Masayoshi Tanaka

Jun Kimura

Takayuki Ishida

Makoto Furuhashi

Hideyuki Saito

Teiji Yutaka

Shinya Wada

Sachiyo Aoki

Daisuke Tahara

Shinichi Honda

Yoshihiro Myokan

Toyoshi Okada

Masayuki Chatani

Takayuki Shinohara

Ryuji Yamamoto

Takahiro Fujii

Hirotoshi Maegawa

Takashi Kohashi

Takashi Itou

Shunsuke Kunieda

Toshiyuki Hiroi

Muneki Shimada

Kenjiro Komaki

Naoki Numaguchi

Yousuke Kimoto

Norio Nagatsuka

Hiromasa Horie

Keiso Shimakawa

Tyler Daniel

Yuta Kimura

Hidehisa Onai

Takahiro Fukuhara

Yoshinori Ohashi

Takeshi Yamagishi

Hideki Oyaizu

Atsushi Kunimatsu

Noriyuki Yamashita

Michinari Kohno

Shinichi Fukushima

Junichi Naoi

Yasuhiro Watari

Nodoka Tokunaga

Toshiro C Watanabe

Hideo Terasawa

Kazuyuki Arimatsu

Ayaka Nakatani

Jun Hiroi

Jiro Amemiya

Naoto Yoshioka

Noriaki Shinoyama

Norihide Kaneko

Masanori Fukumoto

Taeko Sanada

Koji Kaneda

Junichi Asano

Sasaki Nobuo

A feature acquiring sectionobtains feature data of a target person. A matching degree deriving sectionderives a matching degree between the feature data and feature data of a registered user stored in a feature amount database. An identifying sectiondetermines that the target person is the registered user in a case where the matching degree is greater than or equal to a first threshold, and determines that the target person is not the registered user in a case where the matching degree is less than a second threshold smaller than the first threshold. An action management sectionsets an action mode of an acting subject according to the matching degree.

Information processing device and action mode setting method

When a head-mounted display acquires data of a display image generated on the basis of position/posture information of a head of a user at time and given a distortion corresponding to the distortion of an eyepiece lens, the head-mounted display corrects the image on the basis of position/posture information of the head at time t for display. Then, the head-mounted display corrects chromatic aberrations on the basis of actual distortion coefficients of the lens, and outputs the image to a display panel.

Head-mounted display and image display method

An image generation device divides a distorted-image plane into pixel blocks in order to generate a distorted image in consideration of the distortion and chromatic aberration of an eyepiece. In the plane of a source image, the image generation device determines individual RGB sample positions included in the pixel blocks, sets a bounding rectangle containing the individual RGB sample positions, and determines, for example, computation target pixels corresponding to the bounding rectangle. The image generation device calculates the pixel values of, for example, the computation target pixels, interpolates and samples the calculated pixel values, and regards the results of interpolation and sampling as the pixel values of the distorted image.

Image generation device and image generation method

A display device for displaying an image through a lens specifies a position of a pupil of a user on the basis of a gazing point on a display panel. Parameters used to correct lens distortions of images in red, green, and blue included in data of a display image are prepared in association with representative points of gazing points. The display device interpolates parameters on the basis of a positional relation between the position of an actual gazing point or a predicted value thereof and a representative point, and corrects the display image per primary color using the interpolated parameters, thereby correcting chromatic aberrations.

Display device and image display method

A distorted image generating section directly renders an image having a distortion such that a proper image can be seen when viewed through an eyepiece lens. Specifically, the distorted image generating section calculates which position a target pixel on a view screen will be displaced to by the lens, generates a ray of light that passes from a viewpoint through a pixel at a displacement destination, and uses color information obtained by ray tracing as a pixel value of the target pixel.

Image generation device, head-mounted display, and image generation method

In a head-mounted display, an input information acquisition unitreceives selection of content by a user. A frame rate information acquisition unitacquires information relating to a frame rate of the content, and a luminance adjustment unitdetermines display luminance according to the frame rate. A content reproduction unitreproduces an image of the content, and a display unitdisplays the image at the determined luminance.

Head-mounted display and image displaying method

Content data of a display target is acquired in accordance with a user's operations and is used to determine a configuration of a display image. Of the regions to be rendered using fonts in the display image, the region in which a character is to be displaced by a very small amount is determined. The characters targeted for displacement are rendered while being displaced over time in accordance with predetermined displacement rules. The characters not targeted for displacement are rendered in a reference position. With all characters rendered, the display image is completed and output. The processes of Sto Sare repeated until display is terminated.

Image processing apparatus, display image generating method, and font data structure

A feeling deduction unitdeduces a user's feeling. An internal state management unitmanages an internal state of an object and an internal state of a user on the basis of the deduced user's feeling. An action management unitdetermines an action of the object on the basis of the internal state of the object. An output processing unitcauses the object to perform the action determined by the action management unit

Object control system and object control method

An input information acquiring section accepts a user's operation. A texture region acquiring section acquires a region of a display image to be presented by use of a texture. A velocity acquiring section acquires for each pixel a movement velocity vector of the texture on a plane of the display image. A texture referencing section adjusts a reference range in an axial direction of the velocity vector in keeping with a magnitude of the movement velocity, before sampling texel values. A pixel value determining section determines a pixel value on the basis of the texel values. An output section outputs the display image.

Image processing apparatus and display image generating method

In a calibration apparatus, a captured image acquisition unit acquires data of an image of a calibration chart captured by a fish-eye imaging apparatus. A distortion correction unit makes an assumption of a parameter of the imaging apparatus, takes into account a projection system to make a correction, and adjusts the parameter until an image of the original chart is obtained. A pseudo image drawing unit uses model data of a chart to draw a pseudo captured image. A point-of-view adjustment unit compares the pseudo image and the captured image and adjusts a point-of-view position of a virtual camera according to a difference between positions of markers or intervals of patterns to specify a position of the imaging apparatus.

Calibration apparatus, calibration system, and calibration method

A captured image acquisition sectionacquires, from an imaging apparatus, data of a polarized image obtained by capturing a target object and stores the data into an image data storage section. A region extraction sectionof a target object recognition sectionextracts a region in which a figure of the target object is included in the polarized image. A normal line distribution acquisition sectionacquires a distribution of normal line vectors on a target object surface in regard to the extracted region. A model adjustment sectionadjusts a three-dimensional model of the target object stored in a model data storage sectionin a virtual three-dimensional space such that the three-dimensional model conforms to the distribution of the normal line vectors acquired from the polarized image to specify a state of the target object.

Information processing apparatus and target object recognition method

A captured image acquisition sectionacquires, from an imaging apparatus, data of a polarized image obtained by capturing a target object and stores the data into an image data storage section. A normal line distribution acquisition sectionof a region segmentation sectionacquires a distribution of normal line vectors of a subject surface using the polarized image. A region decision sectionevaluates the distribution of normal line vectors with a predetermined criterion indicating stability such as a dispersion and determines a region in which the stability is high as a region of a figure of a subject to segment the image. An output data generation sectioncarries out various processes using a result of the segmentation to generate output data.

Information processing apparatus and image region segmentation method

An operation object includes a polyhedron. The polyhedron includes characteristic surfaces formed by cutting each vertex of a cube at different angles. An information processing apparatus acquires a normal vector of each surface from a polarized image thereof. Further, the information processing apparatus identifies the characteristic surface by defining, as a characteristic amount, an angle formed by an average vector Nof normal vectors N, N, and Nof reference surfaces that orthogonally intersect each other and a normal vector Nof the characteristic surface surrounded by the reference surfaces. The specification result and the normal vectors thereof are used to acquire the position and orientation of the operation object.

Information processing apparatus, information processing system, operation object, and information processing method

In an information processing device, a photographed image acquiring unit acquires an image which has been photographed by a camera attached to a head mount display. A region determining unit predicts a region which a user gazes at in a display image. An image analyzing unit has a first fineness processing unit and a second fineness processing unit, with the former analyzing a region corresponding to the gaze region in the photographed image with a higher fineness than the latter. An information processing unit performs information processing by using the result of analysis. An image generating unit has a first fineness processing unit and a second fineness processing unit, with the former generating a display image on the gaze region with a higher fineness than the latter. An output unit sends data of the display image to the head mount display.

Information processing device, information processing system, and information processing method

[Object] To perform more stable and highly accurate attitude estimation. [Solution] The attitude optimization unit optimizes the articulation position, the angle, the number of articulations, and the like which are attitude parameters of a human body model (tree structure) by a plurality of optimization techniques so as to match a region in which a human body can exist, and switches among a plurality of optimization techniques and uses an optimum technique. Note that optimization techniques include 1. initial value, 2. algorithm, and 3, restriction, and optimization is performed by switching among these three. For example, it is possible to apply the present disclosure to an image processing device that performs image processing of optimizing the articulation position and angle of a human body model.

Image processing device and method

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Kanagawa, Japan

Akio Ohba