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Abstract

A computer vision/image processing method generates a depth map useful in producing a foreground depth mask for 2D/3D image editing. The method uses image data from a plurality of scenes. Feature points on each of the vertical scan lines in each of the scene images are used to search for corresponding feature points on the corresponding vertical lines in other images. The corresponding feature-point search is performed by using a bipartite match network with a feature-point-ordering constraint and a disparity-limit constraint, and produces an individual feature-point depth map for each input image. A sparse feature-point depth map of the scene is obtained after applying a consistency test to all the individual depth maps. A complete feature-point depth map is produced by applying a color property assisted depth propagation process to the sparse feature-point depth map. Foreground and background separation is then conducted in the depth domain by using the order statistics of the depth data extracted the feature-point depth map. A foreground feature-point depth map is obtained from the separation operation. The final foreground depth mask is generated by applying a color aided eight-nearest-neighbor LMS interpolation process to the foreground feature-point depth map.

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