Abstract: A method and apparatus for finding correspondence between portions of two images that first subjects the two images to segmentation by weighted aggregation (10), then constructs directed acylic graphs (16,18) from the output of the segmentation by weighted aggregation to obtain hierarchical graphs of aggregates (20,22), and finally applies a maximally weighted subgraph isomorphism to the hierarchical graphs of aggregates to find matches between them (24). Two algorithms are described; one seeks a one-to-one matching between regions, and the other computes a soft matching, in which is an aggregate may have more than one corresponding aggregate. A method and apparatus for image segmentation based on motion cues. Motion provides a strong cue for segmentation. The method begins with local, ambiguous optical flow measurements. It uses a process of aggregation to resolve the ambiguities and reach reliable estimates of the motion.

Abstract: A method includes reconstructing the 3D shape of an object appearing in an input image using at least one example objects of a collection of example 3D objects and their colors.

Abstract: A method and apparatus for clustering data, particularly regarding an image, that constructs a graph in which each node of the graph represents a pixel of the image, and every two nodes represent neighboring pixels associated by a coupling factor. Block pixels are selected with unselected neighboring pixels coupled with a selected block to form aggregates. The graph is coarsened recursively by performing iterated weighted aggregation to form larger blocks (aggregates) and obtain hierarchical decomposition of the image while forming a pyramid structure over the image. Saliency of segments is detected in the pyramid, and by computing recursively, a degree of attachment of every pixel to each of the blocks in the pyramid. The pyramid is scanned from coarse to fine starting at the level a segment is detected, to lower levels and rebuilding the pyramid before continuing to the next higher level. Relaxation sweeps sharpen the boundaries of a segment.

Abstract: A method and apparatus for finding correspondence between portions of two images that first subjects the two images to segmentation by weighted aggregation (10), then constructs directed acylic graphs (16,18) from the output of the segmentation by weighted aggregation to obtain hierarchical graphs of aggregates (20,22), and finally applies a maximally weighted subgraph isomorphism to the hierarchical graphs of aggregates to find matches between them (24). Two algorithms are described; one seeks a one-to-one matching between regions, and the other computes a soft matching, in which is an aggregate may have more than one corresponding aggregate. A method and apparatus for image segmentation based on motion cues. Motion provides a strong cue for segmentation. The method begins with local, ambiguous optical flow measurements. It uses a process of aggregation to resolve the ambiguities and reach reliable estimates of the motion.

Abstract: A method includes combining at least two 3-D models, given the positions of the models and constraint areas of the models that should not be changed by the combination. The combining includes generating a weighted graph representation of the models at least in a transition volume and including at least a portion of the constraint areas and finding a minimum cut which separates the weighted graph into two cut graphs representing cut versions of the models.

Abstract: A method for choosing an image from a plurality of three-dimensional models which is most similar to an input image is provided.

Abstract: A method and apparatus for clustering data, particularly regarding an image, that constructs a graph in which each node of the graph represents a pixel of the image, and every two nodes represent neighboring pixels associated by a coupling factor. Block pixels are selected with unselected neighboring pixels coupled with a selected block to form aggregates. The graph is coarsened recursively by performing iterated weighted aggregation to form larger blocks (aggregates) and obtain hierarchical decomposition of the image while forming a pyramid structure over the image. Saliency of segments is detected in the pyramid, and by computing recursively, a degree of attachment of every pixel to each of the blocks in the pyramid. The pyramid is scanned from coarse to fine starting at the level a segment is detected, to lower levels and rebuilding the pyramid before continuing to the next higher level. Relaxation sweeps sharpen the boundaries of a segment.