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Proceedings ArticleDOI

Sort, merge, repeat: an algorithm for effectively finding corners in hand-sketched strokes

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TLDR
This paper presents a new multi-pass corner finding algorithm called MergeCF that is based on continually merging smaller stroke segments with similar, larger stroke segments in order to eliminate false positive corners.
Abstract
Free-sketch recognition systems attempt to recognize freely-drawn sketches without placing stylistic constraints on the users. Such systems often recognize shapes by using geometric primitives that describe the shape's appearance rather than how it was drawn. A free-sketch recognition system necessarily allows users to draw several primitives using a single stroke. Corner finding, or vertex detection, is used to segment these strokes into their underlying primitives (lines and arcs), which in turn can be passed to the geometric recognizers. In this paper, we present a new multi-pass corner finding algorithm called MergeCF that is based on continually merging smaller stroke segments with similar, larger stroke segments in order to eliminate false positive corners. We compare MergeCF to two benchmark corner finders with substantial improvements in corner detection.

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Proceedings ArticleDOI

Sketch it, make it: sketching precise drawings for laser cutting

TL;DR: Sketch It, Make It (SIMI) is a modeling tool that enables non-experts to design items for fabrication with laser cutters and combines the strengths of sketch-based interaction with the power of constraint-based modeling.
Journal ArticleDOI

Technical Section: A ShortStraw-based algorithm for corner finding in sketch-based interfaces

TL;DR: IStraw is presented, a corner finding technique based on the ShortStraw algorithm that addresses deficiencies with ShortSt Straw while maintaining its simplicity and efficiency and develops an extension for ink strokes containing curves and arcs.
Proceedings Article

A Sketch Recognition System for Recognizing Free-Hand Course of Action Diagrams

TL;DR: A real-time sketch recognition interface that recognizes 485 freely-drawn military course-of-action symbols that achieves an accuracy of 90% when considering the top 3 interpretations and requiring every aspect of the shape to be correct.
Journal ArticleDOI

Technical Section: A machine learning approach to automatic stroke segmentation

TL;DR: ClassySeg represents a movement away from prior, heuristic-based approaches, toward a more general and extensible technique, and is more accurate than previous techniques for both user-independent and user-optimized training conditions.
Proceedings ArticleDOI

Detection of Arrows in On-Line Sketched Diagrams Using Relative Stroke Positioning

TL;DR: An arrow detector which searches for arrows as arbitrarily shaped connectors between already found symbols as well as a design of an arrow recognizer where the head is detected using relative strokes positioning is proposed.
References
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Proceedings ArticleDOI

Specifying gestures by example

TL;DR: GRANDMA, a toolkit for rapidly adding gestures to direct manipulation interfaces, and the trainable single-stroke gesture recognizer used by GRANDMA are described.
Proceedings ArticleDOI

PaleoSketch: accurate primitive sketch recognition and beautification

TL;DR: A new low-level recognition and beautification system that can recognize eight primitive shapes, as well as combinations of these primitives, with recognition rates at 98.56% and automatically generates beautified versions of these shapes to provide feedback early in the sketching process is proposed.
Proceedings ArticleDOI

Tahuti: a geometrical sketch recognition system for UML class diagrams

TL;DR: Tahuti is a dual-view sketch recognition environment for class diagrams in UML based on a multi-layer recognition framework which recognizes multi-stroke objects by their geometrical properties allowing users the freedom to draw naturally as they would on paper rather than requiring the user to draw the objects in a pre-defined manner.
Proceedings ArticleDOI

SketchREAD: a multi-domain sketch recognition engine

TL;DR: SketchREAD, a multi-domain sketch recognition engine capable of recognizing freely hand-drawn diagrammatic sketches, is presented and it is found that in both domains the use of context to reclassify low-level shapes significantly reduced recognition error over a baseline system that did not reinterpret low- level classifications.
Proceedings ArticleDOI

Visual similarity of pen gestures

TL;DR: A computational model for predicting perceived gesture similarity that correlates 0.56 with observation is derived and will be incorporated into a gesture design tool, which will aid the pen-based UI designer in creating gesture sets that are easier to learn and more memorable.
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