Sibel Tari

Gulce Bal Bozkurt, Sibel Tari

The digital era transformed design paradigms, blurring borders among exploration, ideation, and construction. Crowd generated big digital data emerged as a new material. There appears to be a need for new content creation tools which do not ignore complex interaction among traditionally separate stages and roles. To address this need in picture design, we present an open-source platform called Inspiration Hunter. It facilitates ideation via search-edit by supplying infinitely many dynamic possibilities available through the web without leaving the content creation environment, hence, seamlessly integrates exploration, ideation, and construction. User experiences show that the platform successfully enables reuse of web data both as a conceptual stimulant and as a material available for cut-transform-paste. Extending grammar-based approach to shape design, Inspiration Hunter mediates data-enabled collaborative creativity beyond common intention, time or space.

M. Ferhat Arslan, Sibel Tari

Shape complexity is a hard-to-quantify quality, mainly due to its relative nature. Biased by Euclidean thinking, circles are commonly considered as the simplest. However, their constructions as digital images are only approximations to the ideal form. Consequently, complexity orders computed in reference to circle are unstable. Unlike circles which lose their circleness in digital images, squares retain their qualities. Hence, we consider squares (hypercubes in $\mathbb Z^n$) to be the simplest shapes relative to which complexity orders are constructed. Using the connection between $L^\infty$ norm and squares we effectively encode squareness-adapted simplification through which we obtain multi-scale complexity measure, where scale determines the level of interest to the boundary. The emergent scale above which the effect of a boundary feature (appendage) disappears is related to the ratio of the contacting width of the appendage to that of the main body. We discuss what zero complexity implies in terms of information repetition and constructibility and what kind of shapes in addition to squares have zero complexity.

Asli Genctav, Sibel Tari

For representing articulated shapes, as an alternative to the structured models based on graphs representing part hierarchy, we propose a pixel-based distinctness measure. Its spatial distribution yields a partitioning of the shape into a set of regions each of which is represented via size normalized probability distribution of the distinctness. Without imposing any structural relation among parts, pairwise shape similarity is formulated as the cost of an optimal assignment between respective regions. The matching is performed via Hungarian algorithm permitting some unmatched regions. The proposed similarity measure is employed in the context of clustering a set of shapes. The clustering results obtained on three articulated shape datasets show that our method performs comparable to state of the art methods utilizing component graphs or trees even though we are not explicitly modeling component relations.

Venera Adanova, Sibel Tari

Planar ornaments, a.k.a. wallpapers, are regular repetitive patterns which exhibit translational symmetry in two independent directions. There are exactly $17$ distinct planar symmetry groups. We present a fully automatic method for complete analysis of planar ornaments in $13$ of these groups, specifically, the groups called $p6m, \, p6, \, p4g, \,p4m, \,p4, \, p31m, \,p3m, \, p3, \, cmm, \, pgg, \, pg, \, p2$ and $p1$. Given the image of an ornament fragment, we present a method to simultaneously classify the input into one of the $13$ groups and extract the so called fundamental domain (FD), the minimum region that is sufficient to reconstruct the entire ornament. A nice feature of our method is that even when the given ornament image is a small portion such that it does not contain multiple translational units, the symmetry group as well as the fundamental domain can still be defined. This is because, in contrast to common approach, we do not attempt to first identify a global translational repetition lattice. Though the presented constructions work for quite a wide range of ornament patterns, a key assumption we make is that the perceivable motifs (shapes that repeat) alone do not provide clues for the underlying symmetries of the ornament. In this sense, our main target is the planar arrangements of asymmetric interlocking shapes, as in the symmetry art of Escher.

Asli Genctav, Sibel Tari

Product shape is one of the factors that trigger preference decisions of customers. Congruity of shape elements and deformation of shape from the prototype are two factors that are found to influence aesthetic response, hence preference. We propose a measure to indirectly quantify congruity of different parts of the shape and the degree to which the parts deviate from a sphere, i.e. our choice of the prototype, without explicitly defining parts and their relations. The basic signals and systems concept that we use is the entropy. Our measure attains its lowest value for a volume enclosed by a sphere. On one hand, deformations from the prototype cause an increase in the measure. On the other hand, as deformations create congruent parts, our measure decreases due to the attained harmony. Our preliminary experimental results are consistent with our expectations.

Asli Genctav, Yusuf Sahillioglu, Sibel Tari

Despite being vastly ignored in the literature, coping with topological noise is an issue of increasing importance, especially as a consequence of the increasing number and diversity of 3D polygonal models that are captured by devices of different qualities or synthesized by algorithms of different stabilities. One approach for matching 3D shapes under topological noise is to replace the topology-sensitive geodesic distance with distances that are less sensitive to topological changes. We propose an alternative approach utilising gradual deflation (or inflation) of the shape volume, of which purpose is to bring the pair of shapes to be matched to a \emph{comparable} topology before the search for correspondences. Illustrative experiments using different datasets demonstrate that as the level of topological noise increases, our approach outperforms the other methods in the literature.