Specifying gestures by example
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Curves and surfaces for computer aided geometric design (3rd ed.): a practical guide
Curves and surfaces for computer aided geometric design (3rd ed.): a practical guide
Recognizing multistroke geometric shapes: an experimental evaluation
UIST '93 Proceedings of the 6th annual ACM symposium on User interface software and technology
Recognizing and interpreting diagrams in design
AVI '94 Proceedings of the workshop on Advanced visual interfaces
Recognition of freehand sketches using mean shift
Proceedings of the 8th international conference on Intelligent user interfaces
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Approximation of digital curves with line segments and circular arcs using genetic algorithms
Pattern Recognition Letters
Robust sketched symbol fragmentation using templates
Proceedings of the 9th international conference on Intelligent user interfaces
Sketch based interfaces: early processing for sketch understanding
Proceedings of the 2001 workshop on Perceptive user interfaces
SketchREAD: a multi-domain sketch recognition engine
Proceedings of the 17th annual ACM symposium on User interface software and technology
Scale-space based feature point detection for digital ink
ACM SIGGRAPH 2006 Courses
PaleoSketch: accurate primitive sketch recognition and beautification
Proceedings of the 13th international conference on Intelligent user interfaces
Sketching subdivision surfaces
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
Revisiting ShortStraw: improving corner finding in sketch-based interfaces
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
Iconic and multi-stroke gesture recognition
Pattern Recognition
A curvature estimation for pen input segmentation in sketch-based modeling
Computer-Aided Design
LADDER, a sketching language for user interface developers
Computers and Graphics
Combining geometry and domain knowledge to interpret hand-drawn diagrams
Computers and Graphics
A freehand sketching interface for progressive construction of 3D objects
Computers and Graphics
Automated freehand sketch segmentation using radial basis functions
Computer-Aided Design
Corner detection and curve segmentation by multiresolution chain-code linking
Pattern Recognition
A discrete geometry approach for dominant point detection
Pattern Recognition
Sketch recognition by fusion of temporal and image-based features
Pattern Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ShortStraw: a simple and effective corner finder for polylines
SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling
Technical Section: A machine learning approach to automatic stroke segmentation
Computers and Graphics
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Some recent approaches have been presented as simple and highly accurate corner finders in the sketches including curves, which is useful to support natural human-computer interaction, but these in most cases do not consider tangent vertices (smooth points between two geometric entities, present in engineering models), what implies an important drawback in the field of design. In this article we present a robust approach based on the approximation to parametric cubic curves of the stroke for further radius function calculation in order to detect corner and tangent vertices. We have called our approach Tangent and Corner Vertices Detection (TCVD), and it works in the following way. First, corner vertices are obtained as minimum radius peaks in the discrete radius function, where radius is obtained from differences. Second, approximated piecewise parametric curves on the stroke are obtained and the analytic radius function is calculated. Then, curves are obtained from stretches of the stroke that have a small radius. Finally, the tangent vertices are found between straight lines and curves or between curves, where no corner vertices are previously located. The radius function to obtain curves is calculated from approximated piecewise curves, which is much more noise free than discrete radius calculation. Several tests have been carried out to compare our approach to that of the current best benchmarked, and the obtained results show that our approach achieves a significant accuracy even better finding corner vertices, and moreover, tangent vertices are detected with an Accuracy near to 92% and a False Positive Rate near to 2%.