Nokia Technologies Oy

Nokia Corporation

Aricent, Inc.

Provenance Asset Group LLC

Krishna Govindarao

Soumik Ukil

Gururaj Putraya

Veldandi Muninder

Pranav Mishra

Mithun Uliyar

Ravi Shenoy

Basavaraja S V

Vinod Pathangay

Kopparapu Suman

Pallapothu Shyam Sundera Bala Koteswara Gupta

Ramkishor Korada

Ramakrishna Venkata Meka

Basavaraja S-v

Changyeon Jo

Toka Veeranjaneyalu

Basavaraj S V

Chang-Yeon Jo

In an example embodiment, method, apparatus and computer program product are provided. The method includes accessing image capture parameters of a plurality of component cameras at a first time instant, where the image capture parameters for a respective component camera of the component cameras are determined based on a scene appearing in a field of view (FOV) of the respective component camera. At a second time instant, a change in appearance of one or more objects of the scene from a FOV of a first component camera to a FOV of a second component camera is determined. Upon determining the change of the appearance of the one or more objects at the second time instant, image capture parameters of the second component camera are set based on image capture parameters of the first component camera accessed at the first time instant.

Adaptive control of image capture parameters in virtual reality cameras

A technique for digital stereo imaging is provided. According to an example embodiment, the technique comprises facilitating stereo image capturing means for capturing image data, said stereo image capturing means comprising a first imaging subsystem that comprises a first image sensor arranged to receive light via a first lens and a second imaging subsystem that comprises a second image sensor arranged to receive light via a second lens, wherein said first and second imaging subsystems are arranged such that the optical axes of said first and second lenses are in parallel to each other; reading pixel values from respective light-sensitive areas of said first and second image sensors, comprising reading pixel values for a first image from a first readout area on the first image sensor, reading pixel values for a second image from a second readout area on the second image sensor, and reading pixel values for support data from at least one portion of the light-sensitive area adjacent to the respective readout area on at least one of the first and second image sensors; and deriving disparity information pertaining to said first and second images on basis of said pixel values read for the first image, for the second image and for said support data.

Stereo imaging

In an example embodiment a method, apparatus and computer program product are provided. The method includes determining presence of at least one moving object in a scene based on two or more burst images corresponding to the scene captured by a first camera. One or more portions of the scene associated with the at least one moving object are identified, and, information related to the one or more portions is provided to a second camera. An image of the scene captured by the second camera second camera is received, where a pixel level shutter disposed in front of an image sensor of the second camera is programmed to periodically open and close, throughout a duration of said image capture, for pixels of the image sensor corresponding to the one or more portions of the scene. A deblurred image corresponding to the scene is generated based on the image.

Method, apparatus and computer program product for motion deblurring of images

An apparatus for generating a panoramic image(s) may include a processor and memory storing executable computer code causing the apparatus to at least perform operations including generating a panoramic image(s) based on performing registration on at least two images associated with depth map data and determining an overlap region(s) between the two images within first and second items of depth map data. The computer program code may further cause the apparatus to label the overlap region(s) within the first or second item of depth map data based on generating a virtual seam(s) connecting portions of the two images to generate a composite image. The portions correspond to image data within first and second items of depth map data. The computer program code may further cause the apparatus to blend the seam of the composite image to obtain the panoramic image. Corresponding methods and computer program products are also provided.

Methods, apparatuses and computer program products for generating panoramic images using depth map data

In an example embodiment, method, apparatus and computer program product for improving image and video captures using depth maps of viewfinder depth map, are provided. The method includes facilitating receipt of a viewfinder depth map of a scene, the viewfinder depth map comprising depth information of a plurality of objects in the scene. One or more objects are selected from the plurality of objects based on depth information of the one or more objects in the viewfinder depth map. Two or more images of the scene are facilitated to be captured by at least adjusting focus of a camera corresponding to the depth information of the one or more objects that are selected. In an example, a method also includes facilitating capture of an image of the scene by at least adjusting focus of a camera corresponding to the depth information of the two or more objects that are selected.

Improving focus in image and video capture using depth maps

In an example embodiment, method, apparatus and computer program product are provided. The method includes facilitating receipt of a deconvolved image including a plurality of component images. A guide image is selected from the component images and a cross-filtering is performed of component images other than the guide image to generate filtered component images. The cross-filtering is performed of a component image by iteratively performing, selecting a pixel and a set of neighboring pixels around the pixel in the guide image, computing a set of weights corresponding to the set of neighboring pixels based at least on spatial differences between the pixel and the set of neighboring pixels, and cross-filtering a corresponding pixel of the pixel in the component image based on the set of weights to generate a filtered corresponding pixel in the component image. The filtered component images form a filtered deconvolved image with reduced chromatic aberration.

Method, apparatus and computer program product for reducing chromatic aberrations in deconvolved images

An apparatus for recognizing faces with different illuminations may include a processor and memory storing executable computer program code causing the apparatus to at least perform operations including detecting and extracting face data of a first candidate face of a first image and a second candidate face of a second image. The first image is associated with a first light intensity and the second image associated with a second light intensity different from the first light intensity. The computer program code may further cause the apparatus to analyze face data to determine whether the first candidate face corresponds to an area in the first image that is substantially the same as an area of the second candidate face and evaluate data of the first and second areas to determine whether the first and second candidate faces are valid or invalid faces. Corresponding methods and computer program products are also provided.

Methods, apparatuses and computer program products for efficiently recognizing faces of images associated with various illumination conditions

In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating receipt of an image of a scene and determining a graph based on connecting nodes of the image. The nodes are either pixels or superpixels of the image. The graph is determined by determining one or more connections of a node to one or more nodes belonging to a pre-defined image region around the node in the image. The connections are associated with edge weights that are determined based on at least one of similarity parameters and spatial distances between the node and the one or more nodes. The method includes determining disparity values at the nodes of the image based at least on performing tree based aggregation of a cost volume on the graph, where the cost volume is associated with the image and at least one view image of the scene.

Method, apparatus and computer program product for disparity estimation in images

A method, apparatus and computer program for: receiving a spatial audio input; determining a direction of interest from the spatial audio input; and generating a spatial audio output dependent on the spatial audio input and the direction of interest.

Method, apparatus and computer program for generating an spatial audio output based on an spatial audio input

In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating receipt of primary depth map and plurality of color segments, the primary depth map associated with a first image and a second image that are stereoscopic pair of images of a scene, and the color segments associated with the first image. The method includes generating plurality of disparity planes based on the color segments and the primary depth map. The method includes determining aggregated cost volume between pixels of the first and second images for the disparity planes. The method includes assigning plane labels corresponding to the disparity planes to pixels of the first and second images based on the aggregated cost volume, an individual pixel being assigned a plane label. The method includes generating secondary depth map based on the plane labels assigned to the pixels of the first and second images.

Method, apparatus and computer program product for depth estimation of stereo images

In an example embodiment, a method, apparatus and computer program product are provided. The method includes computing a first cost volume for a light-field image. A first depth map comprising depth information of the plurality of sub-images of the light-field image is computed based on the first cost volume. A first view image comprising reconstruction information is reconstructed based on the depth information of the plurality of sub-images. A second cost volume corresponding to the first cost volume is computed based on the reconstruction information. The second cost volume is filtered based on the first view image to generate an aggregated cost volume. A second depth map is generated based on the aggregated cost volume. The second depth map facilitates generation of a second view image that is associated with a resolution higher than a resolution of the first view image.

Method, apparatus and computer program product for depth estimation

In an example embodiment, method, apparatus and computer program product are provided. The method includes facilitating receipt of first image (I) and second image (I) of a scene. Cost volume between images Iand Ifor set of foreground labels (FL) and set of background labels (BL) is determined that includes matching costs of pixels in Iand corresponding pixels in Ifor FL and BL. Reduced cost volume is determined from the cost volume, including matching costs of pixels in Iand corresponding pixels in Ifor FL and a background label (L) of BL, where matching cost of an individual pixel in Iand corresponding pixel of the individual pixel in Ifor Lincludes minimum matching cost from a set of matching costs of the individual pixel for BL. A disparity map is generated by performing cost aggregation of the reduced cost volume in Iand I

Method, apparatus and computer program product for disparity estimation of foreground objects in images

In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating receipt of a first image and a second image of a scene comprising one or more objects. The method includes detecting the objects in the first image by detecting object point of the objects in the first image. The method includes detecting the object points of the objects in the second image based on detection of the object points of the objects in the first image. Detection of an object point in the second image that corresponds to an object point of the first image comprises searching for the object point on an epipolar line in the second image corresponding to the object point of the first image. The method includes determining disparity values between the objects points in the first image and the object points in the second image.

Method, apparatus and computer program product for object detection and segmentation

In an example embodiment a method, apparatus and computer program product are provided. The method includes facilitating receipt of a first and a second image. A first and a second aggregated cost volume associated with pixels of the first and the second images are determined for a plurality of disparity values. A first and a second disparity maps are generated based on the first and the second aggregated cost volume. A confidence map for disparity values of the first image is generated based on the first aggregated cost volume. One or more infinity regions in the first image are determined based on a number of confident pixels in color segments of the first image. A third disparity map is generated by determining filtered disparity values for the pixels of the first image where filtered disparity values for pixels of the one or more infinity regions are a pre-defined disparity value.

Method, apparatus and computer program product for disparity map estimation of stereo images

In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises filtering incident light by an IR cut-off filter to generate filtered light. The IR cut-off filter comprises a plurality of pixels with pass-band characteristics for visible light wavelengths and is configured to perform stop-band attenuation of near infrared (NIR) wavelengths. The stop-band attenuation is configured to vary based on spatial location of pixels within the IR cut-off filter. The filtered light received from the IR cut-off filter is sensed by the image sensor to generate sensed light. A baseband signal and a modulated NIR signal are determined by performing transformation of the sensed light. A NIR spectrum associated with the incident light is determined by demodulating the modulated NIR signal. A visible spectrum associated with the incident light is determined based on the NIR spectrum and the baseband signal.

Growing community of inventors

Bengaluru, India

Krishna Govindarao