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When artists design imagery to portray a visual scene, they need not just render visual information veridically. They can select the visual cues to portray, and adapt the information each carries. Their results can depart dramatically from natural scenes, but can nevertheless convey visual information effectively, because viewers' perceptual inferences still work flexibly to arrive at a consistent understanding of the imagery.
We suggest that lines in line-drawings can convey information about shape in this indirect way, and work to develop tools for realizing such lines automatically in non-photorealistic rendering. In the figure below, the picture on the left renders silhouettes. The picture in the center renders occluding contours, and shows that contours, on their own, can be quite limited in the information they convey about shape. The picture on the right, however, includes additional lines we call suggestive contours that convey an object's shape consistently and precisely.
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Suggestive contours are distinct from creases and lines along ridges or valleys. They are in some sense an extension of contours to account for "nearby" viewpoints. In the following paper, we introduce suggestive contours by providing three equivalent mathematical characterizations, along with some descriptive results. We also describe algorithms for their computation, and show a number of results and comparisions to alternative approaches.
Extracting suggestive contours requires good estimates of curvature and derivative of curvature. The following paper describes our algorithm for computing these quantities on triangle meshes:
More recently, we have investigated algorithms for efficient extractions of linear features from volume data:
Click here for a bunch of pictures, together with the 3D models from which they were generated.
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