Justin Cuaresma - Academia.edu (original) (raw)

Papers by Justin Cuaresma

Added support for app groups (iOS only)

Universal Access in Human–Computer Interaction. Designing Novel Interactions, 2017

An experimental application called FittsFace was designed according to ISO 9241-9 to compare and ... more An experimental application called FittsFace was designed according to ISO 9241-9 to compare and evaluate facial tracking and camera-based input on mobile devices for accessible computing. A user study with 12 participants employed a Google Nexus 7 tablet to test two facial navigation methods (positional, rotational) and three selection methods (dwell, smile, blink). Positional navigation was superior, with a mean throughput of 0.58 bits/second (bps), roughly 1.5× the value observed for rotational navigation. Blink selection was the least accurate selection method, with a 28.7% error rate. The optimal combination was positional+smile, with a mean throughput of 0.60 bps and the lowest tracking drop rate.

2014 IEEE Games Media Entertainment, 2014

A user study was performed to compare two nontouch input methods for mobile gaming: tilt-input an... more A user study was performed to compare two nontouch input methods for mobile gaming: tilt-input and facial tracking. User performance was measured on a mobile game called StarJelly installed on a Google Nexus 7 HD tablet. The tiltinput method yielded significantly better performance. The mean game-score attained using tilt-input was 665.8. This was 7× × higher than the mean of 95.1 for facial tracking. Additionally, participants were more precise with tilt-input with a mean star count of 19.7, compared to a mean of 1.9 using facial tracking. Although tilt-input was superior, participants praised facial tracking as challenging and innovative.

Three recent Qwerty soft keyboard variations are studied: Curve (equivalent to Swype), T+ (equiva... more Three recent Qwerty soft keyboard variations are studied: Curve (equivalent to Swype), T+ (equivalent to SureType), and Octopus (equivalent to the Blackberry Z10 keyboard). In an experiment with 12 participants, the Octopus keyboard surpassed the standard Qwerty keyboard by the 4 th phrase entered, reaching an entry speed of 70 wpm on the 9 th phrase. The standard Qwerty soft keyboard had a mean entry speed of 54 wpm. The Curve is shown to be the least efficient of the Qwerty variations with a mean entry speed of 35 wpm. It is also the most error prone of the four keyboards. The T+ keyboard is shown, through the power law of learning, that it can surpass the standard Qwerty keyboard in entry speed after about 19 phrases of input.

An experimental application called FittsFace was designed according to ISO 9241-9 to compare and ... more An experimental application called FittsFace was designed according to ISO 9241-9 to compare and evaluate facial tracking and camera-based input on mobile devices for accessible computing. A user study with 12 participants employed a Google Nexus 7 tablet to test two facial navigation methods (positional, rotational) and three selection methods (dwell, smile, blink). Positional navigation was superior, with a mean throughput of 0.58 bits/second (bps), roughly 1.5× the value observed for rotational navigation. Blink selection was the least accurate selection method, with a 28.7% error rate. The optimal combination was positional+smile, with a mean throughput of 0.60 bps and the lowest tracking drop rate.

Added support for app groups (iOS only)

Universal Access in Human–Computer Interaction. Designing Novel Interactions, 2017

An experimental application called FittsFace was designed according to ISO 9241-9 to compare and ... more An experimental application called FittsFace was designed according to ISO 9241-9 to compare and evaluate facial tracking and camera-based input on mobile devices for accessible computing. A user study with 12 participants employed a Google Nexus 7 tablet to test two facial navigation methods (positional, rotational) and three selection methods (dwell, smile, blink). Positional navigation was superior, with a mean throughput of 0.58 bits/second (bps), roughly 1.5× the value observed for rotational navigation. Blink selection was the least accurate selection method, with a 28.7% error rate. The optimal combination was positional+smile, with a mean throughput of 0.60 bps and the lowest tracking drop rate.

2014 IEEE Games Media Entertainment, 2014

A user study was performed to compare two nontouch input methods for mobile gaming: tilt-input an... more A user study was performed to compare two nontouch input methods for mobile gaming: tilt-input and facial tracking. User performance was measured on a mobile game called StarJelly installed on a Google Nexus 7 HD tablet. The tiltinput method yielded significantly better performance. The mean game-score attained using tilt-input was 665.8. This was 7× × higher than the mean of 95.1 for facial tracking. Additionally, participants were more precise with tilt-input with a mean star count of 19.7, compared to a mean of 1.9 using facial tracking. Although tilt-input was superior, participants praised facial tracking as challenging and innovative.

Three recent Qwerty soft keyboard variations are studied: Curve (equivalent to Swype), T+ (equiva... more Three recent Qwerty soft keyboard variations are studied: Curve (equivalent to Swype), T+ (equivalent to SureType), and Octopus (equivalent to the Blackberry Z10 keyboard). In an experiment with 12 participants, the Octopus keyboard surpassed the standard Qwerty keyboard by the 4 th phrase entered, reaching an entry speed of 70 wpm on the 9 th phrase. The standard Qwerty soft keyboard had a mean entry speed of 54 wpm. The Curve is shown to be the least efficient of the Qwerty variations with a mean entry speed of 35 wpm. It is also the most error prone of the four keyboards. The T+ keyboard is shown, through the power law of learning, that it can surpass the standard Qwerty keyboard in entry speed after about 19 phrases of input.

An experimental application called FittsFace was designed according to ISO 9241-9 to compare and ... more An experimental application called FittsFace was designed according to ISO 9241-9 to compare and evaluate facial tracking and camera-based input on mobile devices for accessible computing. A user study with 12 participants employed a Google Nexus 7 tablet to test two facial navigation methods (positional, rotational) and three selection methods (dwell, smile, blink). Positional navigation was superior, with a mean throughput of 0.58 bits/second (bps), roughly 1.5× the value observed for rotational navigation. Blink selection was the least accurate selection method, with a 28.7% error rate. The optimal combination was positional+smile, with a mean throughput of 0.60 bps and the lowest tracking drop rate.