Abstract: Probabilistic determination of selected image portions is described. In one or more implementations, a selection input is received for selecting a portion of an image. For pixels of the image that correspond to the selection input, probabilities are determined that the pixels are intended to be included as part of a selected portion of the image. In particular, the probability that a given pixel is intended to be included as part of the selected portion of the image is determined as a function of position relative to center pixels of the selection input as well as a difference in one or more visual characteristics with the center pixels. The determined probabilities can then be used to segment the selected portion of the image from a remainder of the image. Based on the segmentation of the selected portion from the remainder of the image, selected portion data can be generated that defines the selected portion of the image.

Abstract: Probabilistic determination of selected image portions is described. In one or more implementations, a selection input is received for selecting a portion of an image. For pixels of the image that correspond to the selection input, probabilities are determined that the pixels are intended to be included as part of a selected portion of the image. In particular, the probability that a given pixel is intended to be included as part of the selected portion of the image is determined as a function of position relative to center pixels of the selection input as well as a difference in one or more visual characteristics with the center pixels. The determined probabilities can then be used to segment the selected portion of the image from a remainder of the image.

Abstract: Probabilistic determination of selected image portions is described. In one or more implementations, a selection input is received for selecting a portion of an image. For pixels of the image that correspond to the selection input, probabilities are determined that the pixels are intended to be included as part of a selected portion of the image. In particular, the probability that a given pixel is intended to be included as part of the selected portion of the image is determined as a function of position relative to center pixels of the selection input as well as a difference in one or more visual characteristics with the center pixels. The determined probabilities can then be used to segment the selected portion of the image from a remainder of the image. Based on the segmentation of the selected portion from the remainder of the image, selected portion data can be generated that defines the selected portion of the image.

Abstract: Techniques for focal length warping are described. Focal length warping, for instance, may provide an automated approach for correcting distortion in an input image to improve its perceptual quality. In at least some implementations, a focal length of a camera lens used to capture an image and an estimated camera distance are utilized to three-dimensionally reproject and warp the image to generate an adjusted image simulating a new focal length and a new camera distance. Implementations of focal length warping may estimate a camera distance based on facial features in an image.

Abstract: Probabilistic determination of selected image portions is described. In one or more implementations, a selection input is received for selecting a portion of an image. For pixels of the image that correspond to the selection input, probabilities are determined that the pixels are intended to be included as part of a selected portion of the image. In particular, the probability that a given pixel is intended to be included as part of the selected portion of the image is determined as a function of position relative to center pixels of the selection input as well as a difference in one or more visual characteristics with the center pixels. The determined probabilities can then be used to segment the selected portion of the image from a remainder of the image.

Abstract: Techniques for focal length warping are described. Focal length warping, for instance, may provide an automated approach for correcting distortion in an input image to improve its perceptual quality. In at least some implementations, a focal length of a camera lens used to capture an image and an estimated camera distance are utilized to three-dimensionally reproject and warp the image to generate an adjusted image simulating a new focal length and a new camera distance. Implementations of focal length warping may estimate a camera distance based on facial features in an image.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The computing device also includes a processor configured to execute the instructions to perform a method that includes defining a simulated fluid object that includes a first portion and a second portion being represented by a signed distance function. The method also includes applying at least one constraint to the first portion of the simulated fluid object to match a velocity of a target. The method also includes applying a collection of calculated forces to the second portion of the simulated fluid object. Also, the method includes rendering the first portion applied with the at least one constraint and the second portion applied with the collection of calculated forces to present the simulated fluid object.