Effectively Labeling Planar Projections of Polyhedra
IEEE Transactions on Pattern Analysis and Machine Intelligence
An optimization-based approach to the interpretation of single line drawings as 3D wire frames
International Journal of Computer Vision
The Interpretation of Line Drawings with Contrast Failure and Shadows
International Journal of Computer Vision
Overcoming Superstrictness in Line Drawing Interpretation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Line drawings via abstracted shading
ACM SIGGRAPH 2007 papers
Plane-Based Optimization for 3D Object Reconstruction from Single Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Rich Discrete Labeling Scheme for Line Drawings of Curved Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Line Drawing Interpretation
Technical Section: Sketch-based modeling: A survey
Computers and Graphics
Exploiting artistic cues to obtain line labels for free-hand sketches
Proceedings of the International Symposium on Sketch-Based Interfaces and Modeling
Genetic algorithm for line labeling of diagrams having drawing cues
Diagrams'12 Proceedings of the 7th international conference on Diagrammatic Representation and Inference
Introduction: Foreword to the special section on expressive graphics
Computers and Graphics
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Line drawings are well known to exhibit geometric ambiguities, resulting in, drawings that can have multiple interpretations. However, drawings are used to present design concepts to peers in fields such as engineering design, where it is imperative that the observer interprets the drawing in the same way as the designer for effective communication. Designers therefore use cues, prompting the observer to resolve the geometric ambiguities and achieve the desired interpretation. In this paper, we identify the cues introduced in drawings and focus on two cues, namely table-lines (which convey information about the position of the object in space) and shadows (which convey information about the geometry of the object). These cues can be used in a line-labelling context to allow a line-labelling algorithm to overcome the geometric ambiguities of the drawing. For this purpose, we propose a cue-constrained genetic algorithm that takes the vectorized line drawing and the identified cues attached to each edge, and uses these cues as constraints on the edge labels, thus distinguishing between different object-background interactions. We show that the proposed algorithm can be used to successfully label intentionally ambiguous line drawings according to some desired interpretation as specified by the additional cues present in the drawing.