C4.5: programs for machine learning
C4.5: programs for machine learning
Applying constraints to enforce users' intentions in free-hand 2-D sketches
Intelligent Systems Engineering
Interactive beautification: a technique for rapid geometric design
Proceedings of the 10th annual ACM symposium on User interface software and technology
Machine Learning for the Detection of Oil Spills in Satellite Radar Images
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
A domain-independent system for sketch recognition
Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Concept-Learning in the Presence of Between-Class and Within-Class Imbalances
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Mining with rarity: a unifying framework
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Sketch based interfaces: early processing for sketch understanding
ACM SIGGRAPH 2006 Courses
An efficient graph-based recognizer for hand-drawn symbols
Computers and Graphics
Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes
Proceedings of the 20th annual ACM symposium on User interface software and technology
PaleoSketch: accurate primitive sketch recognition and beautification
Proceedings of the 13th international conference on Intelligent user interfaces
A pen-based tool for efficient labeling of 2D sketches
SBIM '07 Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling
Sort, merge, repeat: an algorithm for effectively finding corners in hand-sketched strokes
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
A curvature estimation for pen input segmentation in sketch-based modeling
Computer-Aided Design
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Combining speech and sketch to interpret unconstrained descriptions of mechanical devices
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Technical Section: SpeedSeg: A technique for segmenting pen strokes using pen speed
Computers and Graphics
ShortStraw: a simple and effective corner finder for polylines
SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling
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We present ClassySeg, a technique for segmenting hand-drawn pen strokes into lines and arcs. ClassySeg employs machine learning techniques to infer the segmentation intended by the drawer. The technique begins by identifying a set of candidate segment points, consisting of all curvature maxima. Features are computed for each candidate point based on speed, curvature, and other geometric properties. These features are adapted from numerous prior segmentation approaches, effectively combining their strengths. These features are used to train a statistical classifier to identify which candidate points are true segment points. A beam search is used to approximate the optimal subset of features to use as input to the classifier. ClassySeg is more accurate than previous techniques for user-independent training conditions, and is as good as the current state-of-the-art algorithm for user-optimized conditions. More importantly, ClassySeg represents a movement away from prior heuristic-based approaches towards a more general and extensible approach.