The output is represented in terms of scalable vector graphics layers, thereby enabling meaningful sketch editing and manipulation. These parts are then considered in a priority-ordered fashion, which enables us to identify and recursively process new shape parts while keeping track of their relative depth ordering. To extract the structure, we introduce a new part-aware metric for complex 2D drawings, the radial variation metric, which is used to identify salient parts. Our method handles drawings that contain complex internal contours with T-junctions indicative of occlusions, as well as internal curves that may either be expressive strokes or substructures. We present a method that automatically extracts salient structure, organized as parts with relative depth orderings, from clean-line vector drawings of smooth organic shapes. The layers correspond to salient regions of the drawing, which are often naturally associated to ‘parts’ of the underlying shape. For clean-line vector drawings of smooth organic shapes, we describe a method to automatically extract a layered structure for the drawn object from the current or nearby viewpoints. The first one is able to infer plausible 3D models of animals from a single side-view sketch using anatomic principles to both interpret the drawing's elements and infer depth offsets between these elements.The second is an approach to decompose depictions of smooth shapes with non trivial cusp points into a set of structural parts' silhouettes ordered in depth, which can be used for editing and animation purposes.Many related ideas were explored on the way, and the ones presented in this manuscript leaves me confident about the future of this field of research.Ĭomplex vector drawings serve as convenient and expressive visual representations, but they remain difficult to edit or manipulate. #Inkscape stroke to path leaves dent freeWe introduce VGC-specific methods that are tailored towards quickly achieving desired stacking orders for faces, edges, and vertices.ĭrawing is the most common way to communicate about shapes.Thus, using sketching as a tool in the process of modeling 3D content is an attractive approach.However in the world of machines, drawings are still difficult to interpret as shape depictions.This has been the challenge tackled by many different research works since leveraging the little we know about perception is non trivial.My thesis focuses on pushing the limits of what can be inferred from single drawings of smooth shapes without any help from the user.In a first attempt we chose to select a category of shape namely animals and other creatures for which prior knowledge helps to solve the problem.Then we proposed to generalize parts of the solution to tackle the case of free form organic shapes.This manuscript thus presents the respective solutions we developed. This allows for the coordinated editing of shared vertices and edges even for objects that have components distributed across multiple layers. Our system maintains a global stacking order for all faces, edges, and vertices without requiring that components of an object reside together on a single layer. We describe and implement a set of topological editing operations for the VGC, including glue, unglue, cut, and uncut. This allows for the direct representation of incidence relationships between objects and can therefore more faithfully capture the intended semantics of many illustrations, while at the same time keeping the geometric flexibility of stacking-based systems. The VGC can represent any arbitrary non-manifold topology as an immersion in the plane, unlike planar maps which can only represent embeddings. We introduce the vector graphics complex (VGC) as a simple data structure to support fundamental topological modeling operations for vector graphics illustrations. Basic topological modeling, such as the ability to have several faces share a common edge, has been largely absent from vector graphics.
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