Abstract: A device, an apparatus and associated methods are provided. In one embodiment, the method comprises obtaining a multi-plane image (MPI) representation of a three dimensional (3D) scene. The MPI representation includes a plurality of slices of content from the 3D scene, each slice corresponding to a different depth relative to a position of a first virtual camera. Each slice is decomposed into regular tiles; and the orientation of each tile is determined.

Abstract: A device, an apparatus and associated methods are provided. In one embodiment, the method comprises obtaining a multi-plane image (MPI) representation of a three dimensional (3D) scene. The MPI representation includes a plurality of slices of content from the 3D scene, each slice corresponding to a different depth relative to a position of a first virtual camera. Each slice is decomposed into regular tiles; and the orientation of each tile is determined.

Abstract: A device includes at least one first sensor and at least one second sensor for capturing first image data, the at least one first and second sensors being rectangular and arranged orthogonal to the at least one first rectangular sensor, and at least one hardware processor configured to cause the at least one first and second sensors, respectively, the first image data and the second image data at least substantially simultaneously, and at least one of display simultaneously data from the first image data and data from the second image data as a cross-shaped image or store together data from the first image data and data from the second image data as a cross-shaped image. The resulting first and second image data can be stored in a single file in memory. The at least one hardware processor can be processed to remove redundancies between the image data. The device can also extract from the first and second image data, image data corresponding to a rectangle parallel with an horizon.

Abstract: A method and system are provided for generating an image from each camera array in a camera array matrix. In one embodiment, the method comprises increasing redundancy between to be captured images from the camera matrix by rotating direction of any cameras disposed in upper and lower rows of said matrix by a 90 degree angle around the roll axis. Then any cameras disposed at the corners of the matrix are rotated in an angle that is less than 90 degrees around the roll axis. Subsequently, the location of central cameras are determined and analysed so that they can be rotated and disposed in a manner that provides both horizontal and vertical compensation for any redundancies.

Abstract: A device, an apparatus and associated methods are provided. In one embodiment, the method comprises obtaining a multi-plane image (MPI) representation of a three dimensional (3D) scene. The MPI representation includes a plurality of slices of content from the 3D scene, each slice corresponding to a different depth relative to a position of a first virtual camera. Each slice is decomposed into regular tiles; and the orientation of each tile is determined.

Abstract: A method and system are provided for generating an image from each camera array in a camera array matrix. In one embodiment, the method comprises increasing redundancy between to be captured images from the camera matrix by rotating direction of any cameras disposed in upper and lower rows of said matrix by a 90 degree angle around the roll axis. Then any cameras disposed at the corners of the matrix are rotated in an angle that is less than 90 degrees around the roll axis. Subsequently, the location of central cameras are determined and analysed so that they can be rotated and disposed in a manner that provides both horizontal and vertical compensation for any redundancies.

Abstract: A device includes at least one first sensor and at least one second sensor for capturing first image data, the at least one first and second sensors being rectangular and arranged orthogonal to the at least one first rectangular sensor, and at least one hardware processor configured to cause the at least one first and second sensors, respectively, the first image data and the second image data at least substantially simultaneously, and at least one of display simultaneously data from the first image data and data from the second image data as a cross-shaped image or store together data from the first image data and data from the second image data as a cross-shaped image. The resulting first and second image data can be stored in a single file in memory. The at least one hardware processor can be processed to remove redundancies between the image data. The device can also extract from the first and second image data, image data corresponding to a rectangle parallel with an horizon.

Abstract: A method is proposed for estimating a depth for pixels in a matrix of M images. Such method comprises, at least for one set of N images among the M images, 2<N?M, a process comprising: —determining depth maps for the images in the set of N images delivering a set of N depth maps; —for at least one current pixel for which a depth has not yet been estimated: —deciding if a candidate depth corresponding to a depth value in the set of N depth maps is consistent or not with the other depth map(s) of the set of N depth maps; —selecting the candidate depth as being the estimated depth for the current pixel if the candidate depth is decided as consistent. The process is enforced iteratively with a new N value which is lower than the previous N value used in the previous iteration of the process.

Abstract: A method is proposed for estimating a depth for pixels in a matrix of M images. Such method comprises, at least for one set of N images among the M images, 2?N?M, a process comprising: —determining depth maps for the images in the set of N images delivering a set of N depth maps; —for at least one current pixel for which a depth has not yet been estimated: —deciding if a candidate depth corresponding to a depth value in the set of N depth maps is consistent or not with the other depth map(s) of the set of N depth maps; —selecting the candidate depth as being the estimated depth for the current pixel if the candidate depth is decided as consistent. The process is enforced iteratively with a new N value which is lower than the previous N value used in the previous iteration of the process.

Abstract: A method and an apparatus for depth-map estimation between at least two images respectively captured by at least two cameras are disclosed. Extrinsic and intrinsic parameters of the at least two cameras are obtained. Local spatial structure descriptors for each pixel of the at least two images are obtained by transforming a patch of pixels surrounding each pixel, and depth is obtained for at least one pixel of a first image among the at least two images, among at least two depth candidates, each depth candidate being associated with a corresponding pixel in a second image of the at least two images, said corresponding pixel in the second image being determined according to the obtained extrinsic and intrinsic parameters.

Abstract: A plenoptic imaging device is described including a micro-lens array placed between a main lens and a photosensor. The micro-lens array has a plurality of micro-lenses each configured to project a micro-image onto the photosensor, the main lens covering a central field-of-view of the scene according to capture axis. The plenoptic imaging device includes multi-faceted optical means structure having at least two facets and placed in a plane adjacent to the aperture diaphragm plane and centered on the main optical axis, each facet being configured to angularly rotated the capture axis with respect to the main optical axis so as to capture a rotated field-of-view from the central field-of-view, and so that the captured rotated field-of-views form an expanded field-of-view covering the central field-of-view.

Abstract: A method and an apparatus for depth-map estimation between at least two images respectively captured by at least two cameras are disclosed. Extrinsic and intrinsic parameters of the at least two cameras are obtained. Local spatial structure descriptors for each pixel of the at least two images are obtained by transforming a patch of pixels surrounding each pixel, and depth is obtained for at least one pixel of a first image among the at least two images, among at least two depth candidates, each depth candidate being associated with a corresponding pixel in a second image of the at least two images, said corresponding pixel in the second image being determined according to the obtained extrinsic and intrinsic parameters.

Abstract: A plenoptic imaging device is described including a micro-lens array placed between a main lens and a photosensor. The micro-lens array has a plurality of micro-lenses each configured to project a micro-image onto the photosensor, the main lens covering a central field-of-view of the scene according to capture axis. The plenoptic imaging device includes multi-faceted optical means structure having at least two facets and placed in a plane adjacent to the aperture diaphragm plane and centered on the main optical axis, each facet being configured to angularly rotated the capture axis with respect to the main optical axis so as to capture a rotated field-of-view from the central field-of-view, and so that the captured rotated field-of-views form an expanded field-of-view covering the central field-of-view.

Abstract: An annotation display assistance device includes a display processing unit that displays images that are possibly included in a first group in relation to a search word; an input accepting unit that accepts a selection of an image that should be included in a second group in relation to the search word among the images displayed by the display processing unit; and an annotation adding unit that detects an image that possibly belongs to the second group among the images displayed by the display processing unit based on the selected image to be included in the second group for adding an annotation associated with the image; wherein the display processing unit displays the annotation associated with the image that is detected to possibly belong to the second group by the annotation adding unit, the annotation indicating that the image possibly belongs to the second group.