摘要:
Model-based stereo matching from a stereo pair of images of a given object, such as a human face, may result in a high quality depth map. Integrated modeling may combine coarse stereo matching of an object with details from a known 3D model of a different object to create a smooth, high quality depth map that captures the characteristics of the object. A semi-automated process may align the features of the object and the 3D model. A fusion technique may employ a stereo matching confidence measure to assist in combining the stereo results and the roughly aligned 3D model. A normal map and a light direction may be computed. In one embodiment, the normal values and light direction may be used to iteratively perform the fusion technique. A shape-from-shading technique may be employed to refine the normals implied by the fusion output depth map and to bring out fine details. The normals may be used to re-light the object from different light positions.
摘要:
Methods and apparatus for soft edge masking. A soft edge masking technique may be provided via which, starting from an initial, potentially very rough and approximate border selection mask, the user may selectively apply brush strokes to areas of an image to selectively improve the border region of the mask, thus providing softness details in border regions which contain soft objects such as hair and fur. A stroke may be an additive stroke indicating a particular region in which detail from an original image is to be added to a composite image, or a subtractive stroke indicating a particular region in which detail is to be removed from the composite image. The stroke may also indicate a strength parameter value that may be used to indicate an amount of bias to be used in opacity calculations for the affected pixels.
摘要:
A method is used for identifying a border in a digital image that is defined by a plurality of pixels, each pixel being defined by a pixel color and a pixel position indicating a location of the pixel in the digital image. The method includes receiving for each pixel a pixel gradient indicating a direction and magnitude of change in color. A user inputs an area of interest that includes at least a portion of the border to be identified. The method then includes estimating information about an edge zone that models the border portion including estimating a position, direction, and width of the edge zone. The position of the edge zone is estimated by calculating a weighted average value of pixel positions of each pixel in the area of interest. The direction of the edge zone is estimated by calculating a weighted average value of pixel gradient direction of each pixel in the area of interest. The method further includes calculating a measure of confidence in the edge zone information and estimating a width of the edge zone at which the calculated measure of confidence decreases appreciably if the estimated width increases. The border is identified based on the estimated edge zone information. An identified border is used to improve masking an object bound by the identified border from the digital image.