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Item Patternista: Learning Element Style Compatibility and Spatial Composition for Ring-based Layout Decoration(The Eurographics Association, 2016) Phan, Huy Quoc; Lu, Jingwan; Asente, Paul; Chan, Antoni B.; Fu, Hongbo; Pierre Bénard and Holger WinnemöllerCreating aesthetically pleasing decorations for daily objects is a task that requires deep understanding of multiple aspects of object decoration, including color, composition and element compatibility. A designer needs a unique aesthetic style to create artworks that stand out. Although specific subproblems have been studied before, the overall problem of design recommendation and synthesis is still relatively unexplored. In this paper, we propose a flexible data-driven framework to jointly consider two aspects of this design problem: style compatibility and spatial composition. We introduce a ring-based layout model capable of capturing decorative compositions for objects like plates, vases and pots. Our layout representation allows the use of the hidden Markov models (HMM's) technique to make intelligent design suggestions for each region of a target object in a sequential fashion. We conducted both quantitative and qualitative experiments to evaluate the framework and obtained favorable results.Item Towards effective evaluation of geometric texture synthesis algorithms(ACM, 2013) AlMeraj, Zainab; Kaplan, Craig S.; Asente, Paul; Forrester Cole and Cindy GrimmIn recent years, an increasing number of example-based Geometric Texture Synthesis (GTS) algorithms have been proposed. However, there have been few attempts to evaluate these algorithms rigorously. We are driven by this lack of validation and the simplicity of the GTS problem to look closer at perceptual similarity between geometric arrangements. Using samples from a geological database, our research first establishes a dataset of geometric arrangements gathered from multiple synthesis sources. We then employ the dataset in two evaluation studies. Collectively these empirical methods provide formal foundations for perceptual studies in GTS, insight into the robustness of GTS algorithms and a better understanding of similarity in the context of geometric texture arrangements.Item Consistent Stylization and Painterly Rendering of Stereoscopic 3D Images(The Eurographics Association, 2012) Northam, Lesley; Asente, Paul; Kaplan, Craig S.; Paul Asente and Cindy GrimmWe present a method for stylizing stereoscopic 3D images that guarantees consistency between the left and right views. Our method decomposes the left and right views of an input image into discretized disparity layers and merges the corresponding layers from the left and right views into a single layer where stylization takes place. We then construct new stylized left and right views by compositing portions of the stylized layers. Because the left and right views come from the same source layers, our method eliminates common artifacts that cause viewer discomfort. We also present a stereoscopic 3D painterly rendering algorithm tailored to our layerbased approach. This method uses disparity information to assist in stroke creation so that strokes follow surface geometry without ignoring painted surface patterns. Finally, we conduct a user study that demonstrates that our approach to stereoscopic 3D image stylization leads to images that are more comfortable to view than those created using other techniques.