Abstract:
The present disclosure includes methods and systems for correcting distortions in spherical panorama digital images. In particular, one or more embodiments of the disclosed systems and methods correct for tilt and/or roll in a digital camera utilized to capture a spherical panorama digital images by determining a corrected orientation and generating an enhanced spherical panorama digital image based on the corrected orientation. In particular, in one or more embodiments, the disclosed systems and methods identify line segments in a spherical panorama digital image, map the line segments to a three-dimensional space, generate great circles based on the identified line segments, and determine a corrected orientation based on the generated great circles.
Abstract:
In embodiments of image color and tone style transfer, a computing device implements an image style transfer algorithm to generate a modified image from an input image based on a color style and a tone style of a style image. A user can select the input image that includes color features, as well as select the style image that includes an example of the color style and the tone style to transfer to the input image. A chrominance transfer function can then be applied to transfer the color style to the input image, utilizing a covariance of an input image color of the input image to control modification of the input image color. A luminance transfer function can also be applied to transfer the tone style to the input image, utilizing a tone mapping curve based on a non-linear optimization to estimate luminance parameters of the tone mapping curve.
Abstract:
In embodiments of image color and tone style transfer, a computing device implements an image style transfer algorithm to generate a modified image from an input image based on a color style and a tone style of a style image. A user can select the input image that includes color features, as well as select the style image that includes an example of the color style and the tone style to transfer to the input image. A chrominance transfer function can then be applied to transfer the color style to the input image, utilizing a covariance of an input image color of the input image to control modification of the input image color. A luminance transfer function can also be applied to transfer the tone style to the input image, utilizing a tone mapping curve based on a non-linear optimization to estimate luminance parameters of the tone mapping curve.
Abstract:
An image processing application performs improved face exposure correction on an input image. The image processing application receives an input image having a face and ascertains a median luminance associated with a face region corresponding to the face. The image processing application determines whether the median luminance is less than a threshold luminance. If the median luminance is less than the threshold luminance, the application computes weights based on a spatial distance parameter and a similarity parameter associated with the median chrominance of the face region. The image processing application then computes a corrected luminance using the weights and applies the corrected luminance to the input image. The image processing application can also perform improved face color correction by utilizing stylization-induced shifts in skin tone color to control how aggressively stylization is applied to an image.
Abstract:
The present disclosure includes methods and systems for correcting distortions in spherical panorama digital images. In particular, one or more embodiments of the disclosed systems and methods correct for tilt and/or roll in a digital camera utilized to capture a spherical panorama digital images by determining a corrected orientation and generating an enhanced spherical panorama digital image based on the corrected orientation. In particular, in one or more embodiments, the disclosed systems and methods identify line segments in a spherical panorama digital image, map the line segments to a three-dimensional space, generate great circles based on the identified line segments, and determine a corrected orientation based on the generated great circles.
Abstract:
Methods and systems are provided for performing material capture to determine properties of an imaged surface. A plurality of images can be received depicting a material surface. The plurality of images can be calibrated to align corresponding pixels of the images and determine reflectance information for at least a portion of the aligned pixels. After calibration, a set of reference materials from a material library can be selected using the calibrated images. The set of reference materials can be used to determine a material model that accurately represents properties of the material surface.
Abstract:
The present disclosure includes methods and systems for modifying orientation of a spherical panorama digital image based on an inertial measurement device. In particular, one or more embodiments of the disclosed systems and methods correct for tilt and/or roll in a digital camera utilized to capture a spherical panorama digital images by detecting changes in orientation to an inertial measurement device and generating an enhanced spherical panorama digital image based on the detect changes. In particular, in one or more embodiments, the disclosed systems and methods modify orientation of a spherical panorama digital image in three-dimensional space based on changes in orientation to an inertial measurement device and resample pixels based on the modified orientation to generate an enhanced spherical panorama digital image.
Abstract:
Systems and methods are provided for content-based selection of style examples used in image stylization operations. For example, training images can be used to identify example stylized images that will generate high-quality stylized images when stylizing input images having certain types of semantic content. In one example, a processing device determines which example stylized images are more suitable for use with certain types of semantic content represented by training images. In response to receiving or otherwise accessing an input image, the processing device analyzes the semantic content of the input image, matches the input image to at least one training image with similar semantic content, and selects at least one example stylized image that has been previously matched to one or more training images having that type of semantic content. The processing device modifies color or contrast information for the input image using the selected example stylized image.
Abstract:
Photometric stabilization for time-compressed video is described. Initially, video content captured by a video capturing device is time-compressed by selecting a subset of frames from the video content according to a frame sampling technique. Photometric characteristics are then stabilized across the frames of the time-compressed video. This involves determining correspondences of pixels in adjacent frames of the time-compressed video. Photometric transformations are then determined that describe how photometric characteristics (e.g., one or both of luminance and chrominance) change between the adjacent frames, given movement of objects through the captured scene. Based on the determined photometric transformations, filters are computed for smoothing photometric characteristic changes across the time-compressed video. Photometrically stabilized time-compressed video is generated from the time-compressed video by using the filters to smooth the photometric characteristic changes.
Abstract:
Photometric stabilization for time-compressed video is described. Initially, video content captured by a video capturing device is time-compressed by selecting a subset of frames from the video content according to a frame sampling technique. Photometric characteristics are then stabilized across the frames of the time-compressed video. This involves determining correspondences of pixels in adjacent frames of the time-compressed video. Photometric transformations are then determined that describe how photometric characteristics (e.g., one or both of luminance and chrominance) change between the adjacent frames, given movement of objects through the captured scene. Based on the determined photometric transformations, filters are computed for smoothing photometric characteristic changes across the time-compressed video. Photometrically stabilized time-compressed video is generated from the time-compressed video by using the filters to smooth the photometric characteristic changes.