Abstract: Disclosed is a decoding method for decoding encoded data obtained by encoding a cube that includes three-dimensional point cloud data. The decoding method includes a step of obtaining point occupation states of solids obtained after division in one direction, from the encoded data, wherein the direction of the division is determined based on correlation among the point occupation states of the solids after the division. Another decoding method and a decoding apparatus are also disclosed.

Abstract: 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.

Abstract: A filter generation method according to one embodiment is a filter generation method for generating a filter for an inter prediction image in moving image coding or video coding, wherein a computer executes a first acquisition procedure for acquiring, for each of subblocks included in a coding object block, a region in a reference image that corresponds to the subblock, a second acquisition procedure for referring to block segmentation information of the reference image and acquiring a coding block that is a block of the reference image which includes the region, and a generation procedure for generating, for the coding object block or each of a plurality of coding object blocks, an image obtained by performing an inverse transformation on one or more coding blocks each acquired in the second acquisition procedure as the filter.

Abstract: A coding method for coding an image to be coded using a reference image includes identifying a reference area being a part of the reference image, the reference area corresponding to an area to be coded being an area obtained by dividing the image to be coded, and obtaining a predicted area with respect to the area to be coded, by prediction using the reference area. The area to be coded and the reference area have different sizes and/or different shapes. In the identifying, the reference area is identified by utilizing a difference between a manner of projection of an object corresponding to the area to be coded and a manner of projection of the object corresponding to the reference area, due to an operation performed on a camera when the image to be coded and the reference image are acquired.

Abstract: A decoding method executed by a decoding device for decoding encoded data from point cloud data includes: acquiring an occupancy code represented in an N (1?N?8)-ary tree structure by decoding the encoded data; repeating a process of generating an N-ary tree structure until a block has a predetermined size, the process being a process in which a cube configured to include all the point cloud data is divided into eight blocks and thereafter when a bit of an occupancy code corresponding to a divided block is 1, the block is further divided; and acquiring, as coordinates of a point in the point cloud data, coordinates of a block of the predetermined size where a bit of an occupancy code corresponding to the block of the predetermined size is 1. In the repeating, the decoding device determines a value of N of the N-ary tree structure for a block to be divided on a basis of an inclusion relation between the block to be divided and a non-occupancy region set in advance.

Abstract: 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.

Abstract: 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.

Abstract: A deep feature generation unit (20) inputs an inference image from an input layer (21) of a neural network, performs forward propagation in the neural network, and outputs a plurality of frame images that each include a channel image and are aligned in a predetermined first sequence as intermediate output values from an intermediate layer (22), which is a predetermined layer that is not an output layer of the neural network. A rearrangement unit (30) rearranges the frame images aligned in the first sequence into frame images in a second sequence based on a predetermined rearrangement sequence from the first sequence to the second sequence, such that a total of degrees of similarity between adjacent frame images in the second sequence is greater than a total of degrees of similarity between adjacent frame images in the first sequence.

Abstract: A video encoding method includes: a provisional image generation step of generating one provisional image from a plurality of frames to be coded; a transformation step of transforming the generated provisional image to a transformed image having the same number of pixels as that of each of the plurality of frames to be coded; and a prediction image generation step of generating a prediction image for each of the frames to be coded, using the transformed image as a reference image.

Abstract: A decoding apparatus includes: an obtainment unit in which a high frame rate, a medium frame rate, and a low frame rate have been determined in advance in descending order of frame rate, and which obtains low-frame-rate images that are moving images with the low frame rate, as well as weights; and a decoding unit that generates a third frame of medium-frame-rate images that are moving images with the medium frame rate by compositing a first frame and a second frame that are chronologically contiguous in the low-frame-rate images based on the weights. The low-frame-rate images and the weights are derived in advance so as to minimize a degree of deviation between a plurality of frames of moving images with the high frame rate in a preset period and a plurality of frames of the medium-frame-rate images in the period.

Abstract: Light having high directivity and high uniformity is emitted. A light source apparatus (10) according to the present invention includes: a light emitting body group (11a) in which a plurality of light sources (11) that emit directional light are arranged on one surface; and a first visual field limiting film (12) that is provided on an optical path of the light emitted from the plurality of light sources (11), and outputs light that enters the first visual field limiting film in a first predetermined angular range by homogeneously diffusing the light within the first predetermined angular range.

Abstract: 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.

Abstract: 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.

Abstract: A learning device includes: a time-series information generation unit that obtains a first image group including a plurality of successive time-series images including a reference image and generates first time-series information based on a difference between the reference image and each of the images in the first image group other than the reference image; and a first learning unit that performs machine learning using the reference image and the first time-series information, thereby obtaining a first learning result used for estimating depth information on a target image, which is an image to be processed, and silhouette information on a subject captured in the target image based on the target image and second time-series information generated from a second image group including a plurality of successive time-series images including the target image.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An image processing apparatus includes a change detection unit that detects phase changes in multiple predetermined directions from among phase changes in a luminance image for each of the mutually different resolutions, and a reliability estimation unit that estimates reliability of the detected phase change based on temporal phase changes in the multiple directions determined in the luminance image. The reliability estimation unit may estimate the reliability based on a diffusion result of the temporal phase changes in the direction. The reliability may become a greater value as the diffusion result indicates more anisotropic.

Abstract: 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.

Abstract: A weight mask generation device includes: a displacement amount derivation unit that derives displacement amounts of feature points in an entire region of a face shape; a separation unit that 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 of the face shape; a normalization unit that derives normalized and separated displacement amounts, which are obtained by normalizing the separated displacement amounts, for every deformation pattern of the partial regions of the face shape; and a weight value generation unit that 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