Gopro, Inc.

Antoine Meler

Bruno César Douady-Pleven

Christophe Clienti

Thomas Derbanne

Adrien Fontvielle

Loïc Martin

Benoit Fouet

Bruno Cesar Douady-Pleven

Julien Morat

Thomas Vuillermet

Yann Renaud Gilquin

Martin Arnoux

Renan Coudray

Denys Bulant

Stéphane Gamet

Emeric Grange

Hervé Bonaillie

Jerome Lehaire

Claire Mathis

Mickaël Heudre

Systems and methods are disclosed for image signal processing. For example, methods may include receiving a first image from a first image sensor, receiving a second image from a second image sensor; obtaining corrected images based on the first image and the second image; obtaining stabilized images based on the corrected images; applying a parallax correction to the stabilized images to obtain a composite image; obtaining a transformed image from the composite image; and encoding an output image based on the transformed image.

Image stitching with electronic rolling shutter correction

Systems and methods are disclosed for image signal processing. For example, methods may include receiving a first image from a first image sensor; receiving a second image from a second image sensor; determining an electronic rolling shutter correction mapping for the first image and the second image; determining a parallax correction mapping based on the first image and the second image for stitching the first image and the second image; determining a warp mapping based on the parallax correction mapping and the electronic rolling shutter correction mapping, wherein the warp mapping applies the electronic rolling shutter correction mapping after the parallax correction mapping; applying the warp mapping to image data based on the first image and the second image to obtain a composite image; and storing, displaying, or transmitting an output image that is based on the composite image.

First visual information defining first spherical visual content, second visual information defining second spherical visual content, and/or other information may be obtained. Presentation of the first spherical visual content on a display may be effectuated. A spherical transition between the first spherical visual content and the second spherical visual content may be identified. The spherical transition may define a change in presentation of visual content on the display from the first spherical visual content to the second spherical visual content based on a transitional motion within a spherical space and/or other information. A change in presentation of the first spherical visual content on the display to presentation of the second visual content on the display may be effectuated based on the spherical transition and/or other information. The change may be determined based on the transition motion within the spherical space and/or other information.

Spherical visual content transition

Images may be obtained using a moving camera comprised of two or more rigidly mounted image sensors. Camera motion may change camera orientation when different portions of an image are captured. Pixel acquisition time may be determined based on image exposure duration and position of the pixel in the image array (pixel row index). Orientation of the sensor may at the pixel acquisition time instance may be determined. Image transformation may be performed wherein a given portion of the image may be associated with a respective transformation characterized by the corrected sensor orientation. In some implementations of panoramic image acquisition, multiple source images may be transformed to, e.g., equirectangular plane, using sensor orientation that is corrected for the time of pixel acquisition. Use of orientation correction may improve quality of stitching by, e.g., reducing contrast of border areas between portions of the transformed image obtained by different image sensors.

Apparatus and methods for rolling shutter compensation for multi-camera systems

Multiple images may be combined to obtain a composite image. Individual images may be obtained with different camera sensors and/or at different time instances. In order to obtain the composite image source images may be aligned in order to produce a seamless stitch. Source images may be characterized by a region of overlap. A disparity measure may be determined for pixels along a border region between the source images. A warp transformation may be determined using a refinement process configured to determine displacement of pixels of the border region based on the disparity. Pixel displacement at a given location may be constrained to direction configured tangential to an epipolar line corresponding to the location. The warp transformation may be propagated to pixels of the image. Spatial and/or temporal smoothing may be applied. In order to obtain refined solution, the warp transformation may be determined at multiple spatial scales.

Apparatus and methods for image alignment

Systems and methods are disclosed for image signal processing. For example, methods may include receiving a first image from a first image sensor; receiving a second image from a second image sensor; stitching the first image and the second image to obtain a stitched image; identifying an image portion of the stitched image that is positioned on a stitching boundary of the stitched image; and inputting the image portion to a machine learning module to obtain a score, wherein the machine learning module has been trained using training data that included image portions labeled to reflect an absence of stitching and image portions labeled to reflect a presence of stitching, wherein the image portions labeled to reflect a presence of stitching included stitching.

Image quality assessment

Images of a scene may be captured by a set of image capture devices. Overlapping areas of the images may be identified based on the topology of the set of image capture devices. Frontiers within the overlapping areas of the images may be identified based on borders of the images. Sample points for the images may be distributed along the frontiers. Warp parameters including an anti-symmetric warping portion and a symmetric warping portion may be determined at the sample points. Displacement values may be determined at the sample points based on the warp parameters. Warp maps for the images may be determined based on diffusion of the displacement values. Displacement maps for the images may be determined based on interpolation of the warp maps. The images may be modified based on the displacement maps.

Systems and methods for parallax compensation

Spherical visual content transitions

Multiple images may be combined to obtain a composite image. Individual images may be obtained with different camera sensors and/or at different time instances. In order to obtain the composite image source images may be aligned in order to produce a seamless stitch. Source images may be characterized by a region of overlap. A disparity measure may be determined for pixels along a border region between the source images. A warp transformation may be determined using an optimizing process configured to determine displacement of pixels of the border region based on the disparity. Pixel displacement at a given location may be constrained to direction configured tangential to an epipolar line corresponding to the location. The warp transformation may be propagated to pixels of the image. Spatial and/or temporal smoothing may be applied. In order to obtain optimized solution, the warp transformation may be determined at multiple spatial scales.

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Chapareillan, France

Antoine Meler