Sony Corporation

Sony Interactive Entertainment Inc.

Sony Computer Entertainment Inc.

Kabushiki Kaisha Toshiba

Sony Corporation Entertainment Inc.

Hiroyuki Segawa

Akio Ohba

Tetsugo Inada

Hidehiko Ogasawara

Hirofumi Okamoto

Katsu Saito

Atsushi Kimura

Yuichi Abe

Shinya Wada

Norikazu Hiraki

Teiyu Goto

Shinichi Honda

Akihiko Sugawara

Takayuki Ishida

Shinya Ishii

Hideyuki Saito

Daisuke Tahara

Yoshihiro Myokan

Akira Suzuki

Hirotoshi Maegawa

Takashi Kohashi

Takashi Itou

Tomokazu Kake

Ryoichi Imaizumi

Kenichiro Nakamura

Hiroyuki Shioya

Naoki Numaguchi

Norio Nagatsuka

Shinichi Kariya

Yukihiro Fukushi

Takeshi Yamagishi

Takayuki Shinohara

Hideki Oyaizu

Nobuo Sasaki

Michinari Kohno

Shogo Sato

Nodoka Tokunaga

Osamu Oda

Miwako Yoritate

Ayaka Nakatani

Jun Hiroi

Akio Yoshioka

Tsuyoshi Hirano

Takayuki Shiomi

Etsuko Morota

Masaharu Fukumoto

Kenichi Konuma

Noriaki Shinoyama

Kayo Kono

Jean-Luc Nougaret

Masanori Fukumoto

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

A sample image obtaining section repetitively obtains a sample image generated by photographing a given sample by a photographing unit. A feature quantity extracting section generates feature quantity data corresponding to the sample image, in reference to the sample image. The feature quantity extracting section classifies each of a plurality of pieces of feature quantity data into either training data or evaluation data. An evaluation learning section performs learning of an evaluation discriminator by using a plurality of pieces of the training data. A photographing necessity/unnecessity determining section determines necessity/unnecessity of additional photographing of the sample by using the evaluation discriminator in which the learning using the plurality of pieces of the training data has already been performed and a plurality of pieces of the evaluation data. A notifying section gives a notification regarding a result of the determination of the necessity/unnecessity of additional photographing of the sample.

Additional photographing necessity/unnecessity notifying apparatus, additional photographing necessity/unnecessity notifying method, and program

In an imaging element, a first light detecting layerincludes an organic photoelectric conversion filmthat detects light of a predetermined wavelength band and carries out photoelectric conversion, and photoelectrically converts incident light on the imaging element and light reflected from a wire grid polarizer layer. The wire grid polarizer layerincludes polarizersin which linear materials that do not allow transmission of light therethrough are arranged at intervals shorter than the wavelength of the incident light. A second light detecting layerincludes photoelectric conversion elementsthat photoelectrically convert light transmitted through the polarizers

Imaging element, image sensor, and information processing apparatus

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 information processing apparatus determines, on the basis of a speech of a user to be evaluated, a reference feature quantity representing a feature of the user's speech at normal times, acquires audio feature quantity data of a target speech to be evaluated made by the user, and evaluates the feature of the target speech on the basis of a comparison result between the audio feature quantity of the target speech and the reference feature quantity.

Information processing apparatus

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

A captured image acquisition section of an information processing apparatus acquires polarization image data including polarization information in a plurality of azimuths. An imaging apparatus information acquisition section acquires information regarding a position and posture of an imaging apparatus. A viewpoint control section of a subject information acquisition section controls a plurality of viewpoints from which polarization images are captured. A point-of-interest information acquisition section sets a pixel of interest having a degree of polarization equal to or higher than a threshold in a polarization image of a first viewpoint, identifies a pixel representing the same point of interest in a polarization image of a second viewpoint, and then obtains a line of intersection between incident planes acquired for the respective viewpoints as a normal vector. An output data generation section generates output data based on results thereof and outputs the data.

Information processing apparatus and subject information acquisition method

Data of a captured image including a polarized image is acquired (S), and space information relating to a position and a posture of a subject in a real space and the position and the posture on an imaging plane is acquired using the captured image data (S). Next, a polarization degree distribution is acquired from a polarized image of a plurality of orientations (S), and a position of a light source is acquired by specifying an image of a true light source by threshold value determination of the polarization degree (S). A reflection characteristic is acquired by applying a rendering equation under assumption that luminance of the captured image is already known (S), and a material suitable therewith is specified as a material of the subject (S). Processing according to the material is performed to generate output data and output the data (S).

Information processing device and material specifying method

A point-of-interest information acquisition section of an information processing apparatus acquires, by using a polarization image captured from a viewpoint of an imaging apparatus, an incident plane relative to the viewpoint at a point of interest 'a' on a subject. A viewpoint control section determines a direction of movement of the imaging apparatus in such a manner as to suitably acquire an angle formed with the incident plane and presents the direction to a user. When the post-movement viewpoint of an imaging apparatus is determined to be appropriate, an incident plane at the point of interest 'a' is acquired by using the captured polarization image, and a line of intersection with the incident plane is assumed to be a normal vector n of the point of interest &#x2018;a.&#x2019;

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

[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

A mat for an image pickup apparatus, where the image pickup apparatus operates to recognize a real object, the mat includes: a play field that defines a bottom region of a space in which the real object is placed; and a calibration chart located in the space and having a plurality of color regions in which respective luminances thereof differ from one another, where: the image pickup apparatus: (i) obtains data of a picked up image of the space in which the real object is located; and (ii) evaluates the picked up image and adjusts at least one of an image pickup condition in which the picked up image of the space is taken, and a processing condition in which the data are analyzed to recognize the real object, and at least one of the image pickup condition and the processing condition are adjusted based on color information in the data of the picked up image resulting from the plurality of color regions of the calibration chart.

Image pickup apparatus, information processing system, mat, and image generation method

An image data generating blockof an image capturing apparatusgenerates polarized images having two or more resolutions from luminance of polarization in two or more directions acquired by a luminance data acquiring block. A pixel value converting blockgenerates new image data with a predetermined parameter being a pixel value on the basis of the polarized luminance in two or more directions. A transmission image generating blockconnects image data of two or more types on a predetermined pixel line basis and then crops the requested data, thereby stream-transferring the cropped data from a communication block. A target object recognizing blockof an information processing apparatusrecognizes the state of a target object by use of the transmitted data and an output data generating blockgenerates output data by use of the recognized state. A communication blockrequests the image capturing apparatusfor the data including type, resolution, and region corresponding to the state of the target object.

Image capturing apparatus, information processing system, information processing apparatus, and polarized-image processing method

An information processing apparatus identifies, by using an audio signal acquired by collecting a user's voice, evaluation target time that includes at least either time not including the user's voice or time during which the user is producing a meaningless utterance and produces an output appropriate to the identified evaluation target time.

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Kanagawa, Japan

Hiroyuki Segawa