Sloppy selection: Providing an accurate interpretation of imprecise selection gestures

Lank, Edward; Saund, Eric

doi:10.1016/j.cag.2005.05.003

Cited by 30 publications

(21 citation statements)

References 8 publications

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“…Finally Lank and Saund present a model of users' pen-based selection gestures to inform the design of a faster, more accurate selection mechanism [LS05]. The results of these previous studies are complementary to our results in the creation of a complete sketch recognition system.…”

Section: Related Worksupporting

confidence: 54%

Designing a sketch recognition front-end

Wais

Wolin

Alvarado

2007

Proceedings of the 4th Eurographics Workshop on Sketch-Based Interfaces and Modeling

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Programs that can recognize students' hand-drawn diagrams have the potential to revolutionize education by breaking down the barriers between diagram creation and simulation. Much recent work focuses on building robust recognition engines, but understanding how to support this new interaction paradigm from a user's perspective is an equally important and less well understood problem. We present a user study that investigates four critical sketch recognition user interface issues: how users integrate the process of triggering recognition into their work, when users prefer to indicate which portions of the diagram should be recognized, how users prefer to receive recognition feedback, and how users perceive recognition errors. We find that user preferences emphasize the importance of system reliability, the minimization of distractions, and the maximization of predictability.

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Section: Related Worksupporting

confidence: 54%

Designing a sketch recognition front-end

Wais

Wolin

Alvarado

2007

Proceedings of the 4th Eurographics Workshop on Sketch-Based Interfaces and Modeling

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“…Note that enhancements introduced with Windows Vista encourage selecting multiple file and folder objects by tapping through the introduction of selection check boxes placed on the objects. Lank and Saund (2005) noted that when users lasso objects, the ''sloppy'' inked path alone may not be the best indicator of their intention. They found that by also using trajectory information, the system can better infer the user's intent.…”

Section: Mackenziementioning

confidence: 96%

Direct Pen Interaction With a Conventional Graphical User Interface

Vogel¹,

Balakrishnan²

2010

Human-Comp. Interaction

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We examine the usability and performance of Tablet PC direct pen input with a conventional graphical user interface (GUI). We use a qualitative observational study design with 16 participants divided into 4 groups: 1 mouse group for a baseline control and 3 Tablet PC groups recruited according to their level of experience. The study uses a scripted scenario of realistic tasks and popular office applications designed to exercise standard GUI components and cover typical interactions such as parameter selection, object manipulation, text selection, and ink annotation. We capture a rich set of logging data including 3D motion capture, video taken from the participants' point-of-view, screen capture video, and pen events such as movement and taps. To synchronize, segment, and annotate these logs, we used our own custom analysis software.We find that pen participants make more errors, perform inefficient movements, and express frustration during many tasks. Our observations reveal overarching problems with direct pen input: poor precision when tapping and dragging, errors caused by hand occlusion, instability and fatigue due to ergonomics and reach, cognitive differences between pen and mouse usage, and frustration due to limited input capabilities. We believe these to be the primary causes of nontext errors, which contribute to user frustration when using a pen with a conventional GUI. Finally, we discuss how researchers could address these issues without sacrificing the consistency of current GUIs and applications by making improvements at three levels: hardware, base interaction, and widget behavior.

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“…We will derive some basic assumptions in our model based on this movement law. Lank and Saund [12] also employed the power law of curvature and its interaction with the steering law [1,3,4] to study pen-based gestures. However, their work is more focused on inferring user's target selection intention from the encircling gestures.…”

Section: Previous Workmentioning

confidence: 99%

Modeling human performance of pen stroke gestures

Cao

Zhai

2007

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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This paper presents a quantitative human performance model of making single-stroke pen gestures within certain error constraints in terms of production time. Computed from the properties of Curves, Line segments, and Corners (CLC) in a gesture stroke, the model may serve as a foundation for the design and evaluation of existing and future gesture-based user interfaces at the basic motor control efficiency level, similar to the role of previous "laws of action" played to pointing, crossing or steeringbased user interfaces. We report and discuss our experimental results on establishing and validating the CLC model, together with other basic empirical findings in stroke gesture production.

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Sloppy selection: Providing an accurate interpretation of imprecise selection gestures

Cited by 30 publications

References 8 publications

Designing a sketch recognition front-end

Designing a sketch recognition front-end

Direct Pen Interaction With a Conventional Graphical User Interface

Modeling human performance of pen stroke gestures

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