Study on the interactive interface design of gaze input smart TV

Chen, Chun-Ching; Lin, Yi-Sin

doi:10.1109/icasi.2018.8394566

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…Murata et al (2013) further compared four Japanese character input methods via fixation on the input interface in terms of input speed, accuracy, simplicity, and fatigue. Chen and Lin (2018) developed an eye‐movement method via fixation to operate a smart television based on expert evaluations and provided design specifications for eye‐control interfaces. Additionally, Cecotti (2016) introduced a novel multi‐mode virtual keyboard and evaluated the changes in its performance when using different modes.…”

Section: Introductionmentioning

confidence: 99%

Improving accuracy of gaze‐control tools: Design recommendations for optimum position, sizes, and spacing of interactive objects

Niu

Zuo

Yang

et al. 2021

Hum Ftrs & Erg Mfg Svc

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To investigate a suitable design of interactive objects in the fixation-triggered eyecontrol interface, this study conducted two ergonomic experiments based on the location of an object, area of the object, and distance between adjacent objects. Experiment 1 investigated the priority distribution of different regions and recommended values of object sizes in different regions. The results showed that middle-middle (MM) area is the optimal area, while middle-left (ML) area, middleright (MR) area, and upper-left (UL) area are suboptimal areas, and the remaining are general areas. The recommended minimum sizes for the optimal area, suboptimal area, and general area are 2.636°(200 px on the screen of a 1920 px × 1080 px 14 inch monitor), 2.978°(225 px on the screen of a 1920 px × 1080 px 14 inch monitor) and 3.322°(250 px on the screen of a 1920 px × 1080 px 14-inch monitor), respectively. Experiment 2 conducted ergonomic experiments of different distances between adjacent objects in horizontal and vertical distributions.The results showed that the appropriate setting of the distribution and size of the objects showed no significant difference between different levels of spacing on the trigger accuracy rate and task completion time. Further, 1.032°(75 px on the screen of a 1920 px × 1080 px 14-inch monitor) could be recommended as the most suitable spacing. According to the conclusions of Experiments 1 and 2, an optimized eye-control interface and the NASA-TLX scale were used to verify the validity and scientificity of the experimental results. The conclusions can be employed to improve the interaction efficiency of the eye-control system and user experience and expand the application field of eye control.

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Section: Introductionmentioning

confidence: 99%

Improving accuracy of gaze‐control tools: Design recommendations for optimum position, sizes, and spacing of interactive objects

Niu

Zuo

Yang

et al. 2021

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

show abstract

“…Enabled by services on demand and applications that support multiple connected systems (games, social networks, internet browsing, etc), the user has an increasing active participation, adapting and interacting with multimedia content. This new paradigm has strong impact on the UX, leading to recent research on the quality and usability of interaction technologies [ 3 , 4 , 5 ]. Conventional TV RCD use mechanical buttons as their main technology for interacting with the user, although this technology provides a limited UX.…”

Section: Introductionmentioning

confidence: 99%

User-Experience with Haptic Feedback Technologies and Text Input in Interactive Multimedia Devices

Silva

Costelha

Bento

et al. 2020

Sensors

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Remote control devices are commonly used for interaction with multimedia equipment and applications (e.g., smart TVs, gaming, etc.). To improve conventional keypad-based technologies, haptic feedback and user input capabilities are being developed for enhancing the UX and providing advanced functionalities in remote control devices. Although the sensation provided by haptic feedback is similar to mechanical push buttons, the former offers much greater flexibility, due to the possibility of dynamically choosing different mechanical effects and associating different functions to each of them. However, selecting the best haptic feedback effects among the wide variety that is currently enabled by recent technologies, remains a challenge for design engineers aiming to optimise the UX. Rich interaction further requires text input capability, which greatly influences the UX. This work is a contribution towards UX evaluation of remote control devices with haptic feedback and text input. A user evaluation study of a wide variety of haptic feedback effects and text input methods is presented, considering different technologies and different number of actuators on a device. The user preferences, given by subjective evaluation scores, demonstrate that haptic feedback has undoubtedly a positive impact on the UX. Moreover, it is also shown that different levels of UX are obtained, according to the technological characteristics of the haptic actuators and how many of them are used on the device.

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“…Of course, some vendors also provide touchscreen interactions to users. Additionally, some recent studies have investigated gaze-based interactive interface design for smart TV apps [4]. However, the way in which a smart TV behaves is still primarily based on a remote control device when it comes to the navigation of the user interface (UI) states.…”

Section: Introductionmentioning

confidence: 99%

EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications

Ahmed

Bureš

2019

IEEE Trans. Consumer Electron.

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Smart TVs are coming to dominate the television market. This accompanied by an increase in the use of the smart TV applications (apps). Due to the increasing demand, developers need modeling techniques to analyze these apps and assess their comprehensiveness, completeness, and quality. In this paper, we present an automated strategy for generating models of smart TV apps based on a black-box reverse engineering. The strategy can be used to cumulatively construct a model for a given app by exploring the user interface in a manner consistent with the use of a remote control device and extracting the runtime information. The strategy is based on capturing the states of the user interface to create a model during runtime without any knowledge of the internal structure of the app. We have implemented our strategy in a tool called EvoCreeper. The evaluation results show that our strategy can automatically generate unique states and a comprehensive model that represents the real user interactions with an app using a remote control device. The models thus generated can be used to assess the quality and completeness of smart TV apps in various contexts, such as the control of other consumer electronics in smart houses.

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Study on the interactive interface design of gaze input smart TV

Cited by 5 publications

References 6 publications

Improving accuracy of gaze‐control tools: Design recommendations for optimum position, sizes, and spacing of interactive objects

Improving accuracy of gaze‐control tools: Design recommendations for optimum position, sizes, and spacing of interactive objects

User-Experience with Haptic Feedback Technologies and Text Input in Interactive Multimedia Devices

EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications

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