Proceedings ArticleDOI
Attribit: content creation with semantic attributes
Siddhartha Chaudhuri,Evangelos Kalogerakis,Stephen Giguere,Thomas Funkhouser +3 more
- pp 193-202
TLDR
Experiments suggest this interface is an effective alternative for novices performing tasks with high-level design goals, enabling rapid, in-situ exploration of candidate designs.Abstract:
We present AttribIt, an approach for people to create visual content using relative semantic attributes expressed in linguistic terms. During an off-line processing step, AttribIt learns semantic attributes for design components that reflect the high-level intent people may have for creating content in a domain (e.g. adjectives such as "dangerous", "scary" or "strong") and ranks them according to the strength of each learned attribute. Then, during an interactive design session, a person can explore different combinations of visual components using commands based on relative attributes (e.g. "make this part more dangerous"). Novel designs are assembled in real-time as the strengths of selected attributes are varied, enabling rapid, in-situ exploration of candidate designs. We applied this approach to 3D modeling and web design. Experiments suggest this interface is an effective alternative for novices performing tasks with high-level design goals.read more
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Semantic shape editing using deformation handles
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