Nokia Technologies Oy

Nokia Corporation

Provenance Asset Group LLC

Veldandi Muninder

Krishna Govindarao

Soumik Ukil

Basavaraja S V

Mithun Uliyar

Pranav Mishra

Gururaj Putraya

Ravi Shenoy

Daniel Vaquero

Hoseok Chang

S V Basavaraja

Basavaraja S-v

Changyeon Jo

Basavaraj S V

Gururaj Gopal Putraya

Chang-Yeon Jo

Krishna Annasagar Govindarao

A method including determining an aggregate cost for pixels in a frame under construction; applying a disparity computation for the pixels in the frame under construction; and storing the frame in a memory. Determining the aggregate cost for the pixels in a frame under construction includes use of at least one previous aggregate cost for the pixels in a previous frame, where the aggregate cost is determined with use of edge-aware filtering and a minimum spanning tree (MST). The disparity computation includes use of a confidence based temporal filtering of disparities at least partially using a disparity computation for the pixels in the previous frame.

Flicker reduction in 3D imaging

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

In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprise assigning weights to at least one first feature and at least one second feature. The at least one first feature may be associated with a first image and the at least one second feature may be associated with a second image. The weights are assigned based on a distance of the at least one first feature and the at least one second feature from a central portion of the corresponding one of the first image and the second image. The method further includes registering the first image and the second image based at least on the assigned weights to determine transforms between the first image and the second image. The first image and the second image may be based on the determined transform.

Method, apparatus and computer program product for generating panorama images

A method, apparatus and computer program product are provided to cause image content to be adjusted in a manner consistent with the corresponding viewing direction, such as the viewing direction of a user of a head-mounted display device. In regards to a method, one or more first anchor frames are determined within a multi-frame image, a user's viewing direction is determined relative to the multi-frame image and at least one second anchor frame is identified based on the user's viewing direction. The method also includes determining one or more tonal modification parameters of a frame in relation to the viewing direction based upon the one or more first anchor frames and the at least one second anchor frame. Further, the method generates a plurality of modified frames based on the one or more tonal modification parameters. A corresponding apparatus and computer program product are also provided.

Method and apparatus for modifying a multi-frame image based upon anchor frames

In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises facilitating a selection of a portion in at least one multimedia frame among a plurality of multimedia frames having a first resolution. The plurality of multimedia frames are partitioned into static layers and dynamic layers based on the selection of the portion. An animated image effect is configured from the dynamic layers of the plurality of multimedia frames. The method further includes performing generation of at least one dynamic frame having a second resolution from the dynamic layers, and, at least one static frame having the second resolution from the static layers. The second resolution is configured to be greater than the first resolution. An animated image having the second resolution is generated based on the at least one dynamic frame and the at least one static frame.

Method, apparatus and computer program product for generating animated images

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

A method, apparatus and computer program product are provided for determining spatial location for one or more facial features. A method computes features for an initial frame. The computed features of the initial frame generate a feature image. A method also determines whether a translation is verified between the initial frame and an intermediate frame, wherein a translation is verified in an instance in which a distance used to verify the translation between the initial frame and the intermediate frame is within a predetermined threshold level. A method also includes a face search, using a portion of the feature image, for one or more facial features, wherein the portion of the feature image searched is a fraction of the total number of frames analyzed in a feature computation cycle. A method also determines a spatial location for the one or more facial features detected in the intermediate frame.

Method and apparatus for feature computation and object detection utilizing temporal redundancy between video frames

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.

Method, apparatus and computer program product for sensing of visible spectrum and near infrared spectrum

Various methods are provided for processing images. One example method may include computing a starting point and an ending point for an image seam as defined by an intersection of a rectangle bounding a first image and a rectangle bounding a second image. The method may also include determining whether the starting point and the ending point for the image seam are final points based on a determined mask region. The method may also include refining the starting point and the ending point by using an intersection of a mask image of the first image and a mask image of the second image in an instance in which it is determined that the starting point and the ending point are not final points. The method may also include computing a seam direction and one or more seam points using the starting point and the ending point.

Method and apparatus for image stitching

A red-eye detection and correction method includes computing a first difference image based on a difference between red pixel intensity and green pixel intensity of a set of pixels. The set of pixels are associated with a first eye region of an image. The method further includes processing the first difference image for computing at least one gradient and at least one projection associated with the at least one gradient. Furthermore, the method includes determining at least one central point based on the at least one projection; and thereafter computing the first eye color defect region based on the at least one central point and a plurality of red pixels of the set of pixels. The method also includes mapping an eye color defect location information computed from a low resolution image to be applicable on the original high resolution image, thereby avoiding recomputation.

Method, apparatus and computer program product for compensating eye color defects

In an example embodiment a method, apparatus and computer program product are provided. The method includes facilitating receipt of two or more images of a scene, where the two or more images are associated with different capture parameters. The method includes determining intensity gains at corresponding pixel locations of at least one image pair of the two or more images. The method further includes generating a blended image by blending pixels of images of the at least one image pair based at least on the intensity gains. A pixel associated with a pixel location of the blended image is generated by blending pixels associated with the pixel location of the images of the at least one image pair.

Growing community of inventors

Bengaluru, India

Veldandi Muninder