Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Emulating the human interpretation of line-drawings as three-dimensional objects
International Journal of Computer Vision
An optimization-based approach to the interpretation of single line drawings as 3D wire frames
International Journal of Computer Vision
Identification of Faces in a 2D Line Drawing Projection of a Wireframe Object
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identifying Faces in a 2D Line Drawing Representing a Manifold Object
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topological analysis of a single line drawing for 3D shape recovery
Proceedings of the 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
A (Sub)Graph Isomorphism Algorithm for Matching Large Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary Search for Faces from Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skewed mirror symmetry detection from a 2D sketch of a 3D model
GRAPHITE '05 Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
A Binary Linear Programming Formulation of the Graph Edit Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Regularity selection for effective 3D object reconstruction from a single line drawing
Pattern Recognition Letters
A template-based reconstruction of plane-symmetric 3D models from freehand sketches
Computer-Aided Design
Skewed rotational symmetry detection from a 2D line drawing of a 3D polyhedral object
Computer-Aided Design
Technical Section: An optimisation-based reconstruction engine for 3D modelling by sketching
Computers and Graphics
A new algorithm for finding faces in wireframes
Computer-Aided Design
Reestablishing consistency of uncertain geometric relations in digital images
Proceedings of the 11th international conference on Theoretical foundations of computer vision
A digital training system for freehand sketch practice
UI-HCII'07 Proceedings of the 2nd international conference on Usability and internationalization
Efficient search of faces from complex line drawings
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Answering subgraph queries over large graphs
WAIM'11 Proceedings of the 12th international conference on Web-age information management
nD object representation and detection from Single 2D line drawing
IWMM'04/GIAE'04 Proceedings of the 6th international conference on Computer Algebra and Geometric Algebra with Applications
nD polyhedral scene reconstruction from single 2D line drawing by local propagation
ADG'04 Proceedings of the 5th international conference on Automated Deduction in Geometry
Precise 3d reconstruction from a single image
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
A general and efficient method for finding cycles in 3D curve networks
ACM Transactions on Graphics (TOG)
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The faces in a 2D fine drawing of an object provide important information for the reconstruction of its 3D geometry. In this paper, a graph-based optimization method is proposed for identifying the faces is a line drawing. The face identification is formulated as a maximum weight clique problem. This formulation is proven to be equivalent to the formulation proposed by Shpitalni and Upson (1996). The advantage of our formulation is that it enables one to develop a much faster algorithm to find the faces in a drawing. The significant improvement in speed is derived from two algorithms provided: the depth-first graph search for quickly generating possible faces from a drawing; and the maximum weight clique finding for obtaining the optimal face configurations of the drawing. The experimental results shown that our algorithm generates the same results of face identification as Shpitalni and Lipson's method, but is much faster when dealing with objects of more than 20 faces