Document Type



Doctor of Philosophy (PhD)


Computer Science

First Advisor's Name

Naphtali Rishe

First Advisor's Committee Title

Co-Committee Chair

Second Advisor's Name

Armando Barreto

Second Advisor's Committee Title

Co-Committee Chair

Third Advisor's Name

Peter Clarke

Fourth Advisor's Name

Raju Rangaswami

Fifth Advisor's Name

Wei Zeng


Human-Computer Interaction, 3D User Interfaces, Multi-Touch, Input Technology, User Experiment, Petri Nets, High-Level Petri Nets, Modeling, Input Recognition, Multi-Touch Recognition, Touch, Gyroscope, 3D Navigation, Primed Search, Feature Extraction, Multi Touch, Augmenting Touch, User Experience, Multi-Touch Displays, Multi-Touch Desktop Display, Non-Stereo Display Touch

Date of Defense



With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display.

The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.



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