Efficiently Capturing Object Contours for Non-Photorealistic Rendering

摘要

Non-photorealistic rendering (NPR) techniques aim to outline the shape of objects and reduce visual clutter such as shadows and inner texture edges. As the first phase result of our entire research, this work is concerned with a structured light based approach that efficiently detects depth edges in real world scenes. Depth edges directly represent object contours. We exploit distortion of the light pattern in the structured light image along depth discontinuities to reliably detect depth edges. However, in reality, distortion along depth discontinuities may not occur or be large enough to detect depending on the distance from the camera or projector. For practical application of the proposed approach, we have presented a novel method that guarantees the occurrence of the distortion along depth discontinuities for a continuous range of object location. Experimental results show a great promise that the technique can successfully provide object contours to be used for non-photorealistic rendering.