Eye gaze assisted human-computer interaction in a hand gesture controlled multi-display environment

Cha, Tong; Maier, Sebastian

doi:10.1145/2401836.2401849

Cited by 7 publications

(2 citation statements)

References 7 publications

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“…Cha and Maier proposed a combination of gaze and mid-air gestures for a multidisplay use case [31]. These authors presented architectural implementation details of their system, but did not present any evaluation results or interaction design decisions.…”

Section: Gaze and Mid-air Gesturesmentioning

confidence: 99%

An Empirical Investigation of Gaze Selection in Mid-Air Gestural 3D Manipulation

Velloso

Turner

Alexander

et al. 2015

Lecture Notes in Computer Science

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Abstract. In this work, we investigate gaze selection in the context of mid-air hand gestural manipulation of 3D rigid bodies on monoscopic displays. We present the results of a user study with 12 participants in which we compared the performance of Gaze, a Raycasting technique (2D Cursor) and a Virtual Hand technique (3D Cursor) to select objects in two 3D mid-air interaction tasks. Also, we compared selection confirmation times for Gaze selection when selection is followed by manipulation to when it is not. Our results show that gaze selection is faster and more preferred than 2D and 3D mid-air-controlled cursors, and is particularly well suited for tasks in which users constantly switch between several objects during the manipulation. Further, selection confirmation times are longer when selection is followed by manipulation than when it is not.

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Section: Gaze and Mid-air Gesturesmentioning

confidence: 99%

An Empirical Investigation of Gaze Selection in Mid-Air Gestural 3D Manipulation

Velloso

Turner

Alexander

et al. 2015

Lecture Notes in Computer Science

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“…The gaze-only input technique often suffers from the so-called “Midas touch” problem [ 32 ]. This problem can be relieved by recognizing the intention based on in-depth processing of gaze tracking data, such as the intended and unintended gaze movement classification [ 33 ], or by introducing an additional modality for confirmation, such as hand gesture [ 34 ], touch action [ 35 – 37 ], joystick [ 38 ] and EEG (electroencephalography) [ 39 ]. As these previous studies aimed to utilize the gaze as an input method, it is more important to recognize the user intention accurately after the actual command action than before the command action.…”

Section: Introductionmentioning

confidence: 99%

Gaze-Assisted User Intention Prediction for Initial Delay Reduction in Web Video Access

Lee

Yoo

Han

2015

Sensors

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Despite the remarkable improvement of hardware and network technology, the inevitable delay from a user's command action to a system response is still one of the most crucial influence factors in user experiences (UXs). Especially for a web video service, an initial delay from click action to video start has significant influences on the quality of experience (QoE). The initial delay of a system can be minimized by preparing execution based on predicted user's intention prior to actual command action. The introduction of the sequential and concurrent flow of resources in human cognition and behavior can significantly improve the accuracy and preparation time for intention prediction. This paper introduces a threaded interaction model and applies it to user intention prediction for initial delay reduction in web video access. The proposed technique consists of a candidate selection module, a decision module and a preparation module that prefetches and preloads the web video data before a user's click action. The candidate selection module selects candidates in the web page using proximity calculation around a cursor. Meanwhile, the decision module computes the possibility of actual click action based on the cursor-gaze relationship. The preparation activates the prefetching for the selected candidates when the click possibility exceeds a certain limit in the decision module. Experimental results show a 92% hit-ratio, 0.5-s initial delay on average and 1.5-s worst initial delay, which is much less than a user's tolerable limit in web video access, demonstrating significant improvement of accuracy and advance time in intention prediction by introducing the proposed threaded interaction model.

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Multimodal Input for Perceptual User Interfaces

LaViola

Buchanan²,

Pittman³

2014

Interactive Displays

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Eye gaze assisted human-computer interaction in a hand gesture controlled multi-display environment

Cited by 7 publications

References 7 publications

An Empirical Investigation of Gaze Selection in Mid-Air Gestural 3D Manipulation

An Empirical Investigation of Gaze Selection in Mid-Air Gestural 3D Manipulation

Gaze-Assisted User Intention Prediction for Initial Delay Reduction in Web Video Access

Multimodal Input for Perceptual User Interfaces

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