Pen-based Interfaces for Engineering and Education

Stahovich, Thomas F.

doi:10.1007/978-1-84882-812-4_5

Cited by 5 publications

(5 citation statements)

References 26 publications

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“…Descriptor: [{Z (1) pq }, {Z (2) pq }] + Biprimitive Figure 4: An example of DZM descriptor for a biprimitive (two channels).…”

Section: Channel 2 Channelmentioning

confidence: 99%

“…It is a natural and efficient means of capturing information by automatically interpreting hand-drawn sketches and it can be the import part of the early design process, where it helps people explore rough ideas and solutions in an informal environment. Sketch recognition has been successfully applied in education [1,2], engineering [2,3], design [4], and so on.…”

Section: Introductionmentioning

confidence: 99%

“…It obtains high recognition accuracy in real time even when the hand-drawn symbols are highly incomplete. (2) We also present two novel descriptors, to represent the spatial distribution between two primitives. One is called DAR (directional adaptive region descriptor), which is not invariant to rotation.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Primitive-Based Method to Recognize Online Sketched Symbols with Autocompletion

You-gen²,

Yang

2015

Mathematical Problems in Engineering

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We present a new structural method of sketched symbol recognition, which aims to recognize a hand-drawn symbol before it is fully completed. It is invariant to scale, stroke number, and order. We also present two novel descriptors to represent the spatial distribution between two primitives. One is invariant to rotation and the other is not. Then a symbol is represented as a set of descriptors. The distance between the input symbol and the template one is calculated based on the assignment problem. Moreover, a fast nearest neighbor (NN) search algorithm is proposed for recognition. The method achieves a satisfactory recognition rate in real time.

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“…Descriptor: [{Z (1) pq }, {Z (2) pq }] + Biprimitive Figure 4: An example of DZM descriptor for a biprimitive (two channels).…”

Section: Channel 2 Channelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Efficient Primitive-Based Method to Recognize Online Sketched Symbols with Autocompletion

You-gen²,

Yang

2015

Mathematical Problems in Engineering

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“…The major limitations of Rubine's recognizer are its sensitivity to the drawing direction, scale, and orientation and inability to identify multi-stroke sketches. Pereira et al [3] made some modifications to Rubine's recognizer in order to make the algorithm accept multi-stroke sketches, but only when drawn with a constant set of strokes, as pointed out by Stahovich [4]. Pereira et al also present a way to make the algorithm insensitive to drawing direction.…”

Section: A Sketch Recognizersmentioning

confidence: 99%

SketchyDynamics: A Library for the Development of Physics Simulation Applications with Sketch-Based Interfaces

Costa¹,

Pereira²

2013

IJIMAI

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-Sketch-based interfaces provide a powerful, natural and intuitive way for users to interact with an application. By combining a sketch-based interface with a physically simulated environment, an application offers the means for users to rapidly sketch a set of objects, like if they are doing it on piece of paper, and see how these objects behave in a simulation. In this paper we present SketchyDynamics, a library that intends to facilitate the creation of applications by rapidly providing them a sketch-based interface and physics simulation capabilities. SketchyDynamics was designed to be versatile and customizable but also simple. In fact, a simple application where the user draws objects and they are immediately simulated, colliding with each other and reacting to the specified physical forces, can be created with only 3 lines of code. In order to validate SketchyDynamics design choices, we also present some details of the usability evaluation that was conducted with a proof-of-concept prototype.

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“…Although the Hausdorff distance has been found to work well when matching templates in computer vision, researchers have mentioned it being sensitive to outliers [39,43]. However, we decided to include it in our testing due to other works using it for gesture recognition [19].…”

Section: Gesture Metricsmentioning

confidence: 99%

Small gestures go a long way

Vatavu

2012

Proceedings of the Designing Interactive Systems Conference

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We investigate in this work the effect of bit depth on the performance of today's commonly used nearest-neighbor gesture recognizers. As current bit representations are typically an artifact of today's hardware and file formats, they are not reflective of the true cardinality of gesture data. We show that as few as 4-5 bits per gesture channel (x/y) are enough in order to attain peak recognition for Euclidean, Cosine, DTW, and Hausdorff distances. We also show how reduction in bit depth can lead to 85 times less memory for storing the training set without ruining recognition performance. The results will benefit practitioners of the next age of gesture sensing gadgets and devices that need to optimize speed, memory, and bit depth representation in their software and hardware designs.

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Pen-based Interfaces for Engineering and Education

Cited by 5 publications

References 26 publications

An Efficient Primitive-Based Method to Recognize Online Sketched Symbols with Autocompletion

An Efficient Primitive-Based Method to Recognize Online Sketched Symbols with Autocompletion

SketchyDynamics: A Library for the Development of Physics Simulation Applications with Sketch-Based Interfaces

Small gestures go a long way

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