Nippon Telegraph and Telephone Corporation

Nagoya University

Hideaki Kimata

Shinya Shimizu

Kazuto Kamikura

Yoshiyuki Yashima

Megumi Isogai

Masaki Kitahara

Dan Mikami

Ayumi Matsumoto

Kazuki Okami

Munekazu Date

Shiori Sugimoto

Kosuke Takahashi

Mariko Isogawa

Akira Kojima

Shoichiro Takeda

Masayuki Tanimoto

Masaaki Matsumura

Kenji Yamamoto

Toshiaki Fujii

Takayuki Kurozumi

Hajime Noto

Yasuhiro Tomita

Seishi Takamura

Ryuichi Tanida

Mayuko Watanabe

Takaaki Akimoto

Norihiko Matsuura

Tadashi Ichikawa

Yoko Sogabe

Tsukasa Kimura

Akio Kameda

Takasuke Nagai

Akihiko Takashima

Ryota Suzuki

An image processing apparatus includes a change detection unit configured to detect color or luminance change for each of different resolutions among changes in color or luminance in a color or luminance image, and a reliability estimation unit configured to estimate reliability of the detected color or luminance change based on temporal color or luminance change in the color or luminance image. The reliability estimation unit estimates the reliability based on a diffusion result of the temporal color or luminance change in the color or luminance image. The reliability has a greater value when the diffusion result shows anisotropy.

Video magnification using anisotropy measure for noise reduction

A decoding method is a decoding method performed by a decoding device, the decoding method including steps of: acquiring, from among a plurality of slice numbers indicating a plurality of slices associated with encoded data of the entire point cloud distributed in a three-dimensional space, a first slice number indicating a first slice associated with encoded data of a point cloud of a first space that is a portion of the three-dimensional space, on the basis of a pointer indicating the first slice; and acquiring the encoded data of the point cloud of the first space on the basis of the first slice number, and decoding point cloud data of the first space from the encoded data of the point cloud of the first space.

Decoding method, decoding apparatus and program for decoding part of an entire point cloud in a three-dimensional space

A camera parameter estimating device includes an obtaining unit which obtains time series frames including a plurality of subject images existing in a common field of vision shared by multiple cameras for each of the cameras, a point estimating unit which estimates the coordinates of a joint point determined in the subject image in the time-series frame for each of the subject images, a motion trajectory estimating unit which estimates the trajectory of the joint point between the time-series frames for each of the cameras, an inter-camera correspondence estimating unit which estimates a group of the trajectories between the frames obtained respectively from a pair of the cameras, and a parameter estimating unit which estimates a camera parameter for each of the cameras according to the group of trajectories.

Camera parameter estimation apparatus, camera parameter estimation method, and camera parameter estimation program

An image coding method includes: an image acquisition step of acquiring a coding-target image; a feature map generation step of generating a feature map, based on the image; a contraction function generation step of performing fractal compression of the feature map and generating a contraction function; and an entropy encoding step of performing entropy encoding of the contraction function.

Image encoding method, image decoding method, image encoding apparatus, image decoding apparatus and program

A unit derives displacement amounts of feature points in an entire region of a face shape. A unit derives separated displacement amounts, each of which is a displacement amount of each feature point for every deformation pattern of a partial region of the face shape, based on the displacement amounts of the feature points in the entire region of the face shape and deformation degrees for every deformation pattern of the partial regions. A unit derives normalized and separated displacement amounts, which are obtained by normalizing the separated displacement amounts, for every deformation pattern of the partial regions. A unit generates weight values of the feature points in the entire region of the face shape based on the normalized and separated displacement amounts for every deformation pattern of the partial regions of the face shape and the deformation degrees for every deformation pattern of the partial regions.

Weighted mask generating apparatus, weighted mask generating method and program

A camera parameter derivation apparatus for deriving camera parameters of a plurality of cameras for which conditions that the cameras be arranged at ideal positions that are set on a straight line at equal intervals and that directions of all arranged cameras be parallel to each other have been set includes an internal parameter derivation unit that derives internal parameter matrices of the cameras based on estimated internal parameter matrices for all cameras that are arranged at estimated positions while being oriented in estimated directions, a camera position derivation unit that derives ideal positions of the cameras that minimize the maximum of the distances between the estimated positions and the ideal positions, and a rotation matrix derivation unit that derives rotation matrices for correcting external parameters such that errors from parallel directions are equal to or less than a threshold value.

Camera parameter derivation apparatus, camera parameter derivation method, and camera parameter derivation program

Provided is a signal reconstruction method executed by a signal reconstruction apparatus including a processor and a memory that stores a codec. The signal reconstruction method includes reconstructing an input signal according to a desired purpose, and in the reconstructing, a likelihood of the input signal being a predetermined type of signal is considered by executing coding on a processing result of the input signal, based on the codec previously determined according to a type of the input signal.

Signal reconstruction method, signal reconstruction apparatus, and program

A virtual reality system is provided that includes a video presentation apparatus, the virtual reality system comprising: the video presentation apparatus which includes circuitry configured to: obtain as input a video sequence composed of a plurality of frames and mask information specifying a complementation target region in the video sequence; separate a frame into a foreground region and a background region based on binary images representing differences between the plurality of frames included in the video sequence; determine either one of patch-search-based completion and paste synthesis as a complementation method for the complementation target region based on a number of pixels belonging to the foreground region and located within a given distance from a periphery of the complementation target region; and complement the complementation target region in accordance with the complementation method; and a virtual reality head mounted display which presents the complemented video sequence to the user.

Virtual environment construction apparatus, video presentation apparatus, model learning apparatus, optimal depth decision apparatus, methods for the same, and program

An image processing apparatus includes a change detection unit configured to detect phase changes in multiple predetermined directions from among phase changes in a luminance image in units of mutually different resolutions, and a reliability estimation unit configured to estimate reliability of the detected phase change based on temporal amplitude change information in the multiple directions determined in the luminance image. The reliability estimation unit may estimate the reliability using an amplitude change of multiple resolutions and using a value of an amplitude change equal to or greater than a predetermined threshold value among images having multiple resolutions. The reliability may become a greater value as the amplitude change becomes larger.

Image processing apparatus, image processing method, and program

An image processing apparatus includes a change detection unit configured to detect a direction change, which is a temporal fluctuation in a plausible direction orthogonal to an edge determined for each pixel in an edge image indicating a high frequency component in an image that is an image processing target, and a phase change, which is a temporal fluctuation of a phase of the high frequency component according to the direction change, and a reliability estimation unit configured to estimate reliability indicating that the detected phase change is not a change caused by noise based on a variance value of the direction change per unit time.

A skeletal information threshold setting apparatus includes: a joint information input unit that accepts an input of important joints among joints of a subject and a confidence threshold for the important joints; and a threshold setting unit that acquires a confidence threshold for each of multiple joints of the subject, including the important joints, based on the important joints and the confidence threshold for the important joints that were input, and sets the acquired confidence thresholds for the joints as thresholds to be used in making a determination regarding a skeletal estimation result for the subject.

Skeleton information determination apparatus, skeleton information determination method and computer program

Provided is technology for extracting a person region from an image, that can suppress preparation costs of learning data. Included are a composited learning data generating unit that generates, from already-existing learning data that is a set of an image including a person region and a mask indicating the person region, and a background image to serve as a background of a composited image, composited learning data that is a set of a composited image and a compositing mask indicating a person region in the composited image, and a learning unit that learns model parameters using the composited learning data. The composited learning data generating unit includes a compositing parameter generating unit that generates compositing parameters that are a set of an enlargement factor, a degree of translation, and a degree of rotation, using the mask of the learning data, and a composited image and compositing mask generating unit that extracts a compositing person region from an image in the learning data using a mask of the learning data, generates the composited image from the background image and the compositing person region, using the compositing parameters, generates the compositing mask from a mask generating image and the compositing person region that are the same size as the composited image, using the compositing parameters, and generates the composited learning data.

Region extraction model learning apparatus, region extraction model learning method, and program

A motion classification model learning apparatus that learns a model for early recognizing a motion is provided. A training data acquisition part acquiring training data configured with pairs of video information about a motion that can be classified into any of a plurality of categories according to characteristics of the motion and category information that is a correct label corresponding to the video information; a motion history image generation part generation a motion history image of the video information; and a model learning part learning a model that outputs a label that is the category information, with the motion history image as an input are included.

Motion classification model learning apparatus, motion classification apparatus, motion classification model learning method and program

A subject tracking device includes a first histogram generation unit configured to generate a first histogram representing an appearance frequency of an image feature quantity of a subject region, for each segment and for each auxiliary segment of the image feature quantity, a second histogram generation unit configured to generate, for each candidate region, a second histogram representing an appearance frequency of the image feature quantity of an image of a candidate region for each segment and for each auxiliary segment of the image feature quantity, a difference derivation unit configured to compare the first histogram with the second histogram for each segment and for each auxiliary segment, and derive, for each candidate region, a total difference value of the appearance frequencies of the image feature quantities of the first histogram and the second histogram; and a region selection unit configured to select the candidate region having a minimum total difference value from among the candidate regions. The auxiliary segment is defined to straddle boundaries between the segments.

Object tracking apparatus, object tracking method and program

An image processing apparatus includes a change detection unit configured to detect a phase change having a predetermined amount of change from phase changes in a subregion of an edge image having a predetermined resolution, a change amount adjustment unit configured to adjust the amount of change of the detected phase change, an adjusted image generation unit configured to generate an edge image having the predetermined resolution in which the amount of change of a motion change is adjusted based on the phase change in which the amount of change of the phase change is adjusted, and a region decision unit configured to decide a new subregion of an edge image having a new predetermined resolution based on the edge image having the predetermined resolution in which the amount of change of the motion change is not adjusted and the edge image having the predetermined resolution in which the amount of change of the motion change is adjusted.

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Yokosuka, Japan

Hideaki Kimata