We propose a real-time rendering system for automatically creating a caricature drawing, i.e., an exaggerated portrait, of a human face, based on simultaneous use of a range image (or 3D mesh) and a registered photogr...We propose a real-time rendering system for automatically creating a caricature drawing, i.e., an exaggerated portrait, of a human face, based on simultaneous use of a range image (or 3D mesh) and a registered photograph of the same face. Combining these information sources provides complementary information. Significant geometric lines such as occluding contours and suggestive contours are extracted from the range data, while textured areas corresponding to shading features are extracted from the photograph. These are combined, and then distorted to produce the final caricature. The final output may be produced using a choice of non-photorealistic rendering styles. Our system method works well for low resolution range images; for these it is fast enough to allow the viewpoint to be chosen in real time. The final output combines significant lines, textured areas, and optional shading, giving a pleasing result which preserves not only the shape cues of the geometric description, but also other essential visual characteristics of the facial image that cannot be deduced from geometry alone.展开更多
We propose a novel technique to extract features from a range image and use them to produce a 3D pen-and-ink style portrait similar to a traditional artistic drawing. Unlike most previous template-based, component-bas...We propose a novel technique to extract features from a range image and use them to produce a 3D pen-and-ink style portrait similar to a traditional artistic drawing. Unlike most previous template-based, component-based or example-based face sketching methods, which work from a frontal photograph as input, our system uses a range image as input. Our method runs in real-time for models of moderate complexity, allowing the pose and drawing style to be modified interactively. Portrait drawing in our system makes use of occluding contours and suggestive contours as the most important shape cues. However, current 3D feature line detection methods require a smooth mesh and cannot be reliably applied directly to noisy range images. We thus present an improved silhouette line detection algorithm. Feature edges related to the significant parts of a face are extracted from the range image, connected, and smoothed, allowing us to construct chains of line paths which can then be rendered as desired. We also incorporate various portrait-drawing principles to provide several simple yet effective non- photorealistic portrait renderers such as a pen-and-ink shader, a hatch shader and a sketch shader. These are able to generate various life-like impressions in different styles from a user-chosen viewpoint. To obtain satisfactory results, we refine rendered output by smoothing changes in line thickness and opacity. We are careful to provide appropriate visual cues to enhance the viewer's comprehension of the human face. Our experimental results demonstrate the robustness and effectiveness of our approach, and further suggest that our approach can be extended to other 3D geometric objects.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 61003149 and U1035004)the Natural Science Foundation of Shandong Province, China (No. ZR2010FQ011)
文摘We propose a real-time rendering system for automatically creating a caricature drawing, i.e., an exaggerated portrait, of a human face, based on simultaneous use of a range image (or 3D mesh) and a registered photograph of the same face. Combining these information sources provides complementary information. Significant geometric lines such as occluding contours and suggestive contours are extracted from the range data, while textured areas corresponding to shading features are extracted from the photograph. These are combined, and then distorted to produce the final caricature. The final output may be produced using a choice of non-photorealistic rendering styles. Our system method works well for low resolution range images; for these it is fast enough to allow the viewpoint to be chosen in real time. The final output combines significant lines, textured areas, and optional shading, giving a pleasing result which preserves not only the shape cues of the geometric description, but also other essential visual characteristics of the facial image that cannot be deduced from geometry alone.
基金Supported by the National Basic Research Program of China (Grant No.2006CB303102)the National Natural Science Foundation of China (Grant Nos.60473103 and 60703028)
文摘We propose a novel technique to extract features from a range image and use them to produce a 3D pen-and-ink style portrait similar to a traditional artistic drawing. Unlike most previous template-based, component-based or example-based face sketching methods, which work from a frontal photograph as input, our system uses a range image as input. Our method runs in real-time for models of moderate complexity, allowing the pose and drawing style to be modified interactively. Portrait drawing in our system makes use of occluding contours and suggestive contours as the most important shape cues. However, current 3D feature line detection methods require a smooth mesh and cannot be reliably applied directly to noisy range images. We thus present an improved silhouette line detection algorithm. Feature edges related to the significant parts of a face are extracted from the range image, connected, and smoothed, allowing us to construct chains of line paths which can then be rendered as desired. We also incorporate various portrait-drawing principles to provide several simple yet effective non- photorealistic portrait renderers such as a pen-and-ink shader, a hatch shader and a sketch shader. These are able to generate various life-like impressions in different styles from a user-chosen viewpoint. To obtain satisfactory results, we refine rendered output by smoothing changes in line thickness and opacity. We are careful to provide appropriate visual cues to enhance the viewer's comprehension of the human face. Our experimental results demonstrate the robustness and effectiveness of our approach, and further suggest that our approach can be extended to other 3D geometric objects.