Although computers are smaller and more readily accessible today than they have ever been, I believe that we have barely scratched the surface of what computers can become. When we use computing devices today, we end up spending a lot of our time navigating to particular functions or commands to use devices their way rather than executing those commands immediately. In this dissertation, I explore what I call unmediated interaction, the notion of people using computers as if the computers are not there and as if the people are using their own abilities or powers instead. I argue that facilitating unmediated interaction via personalization, new input modalities, and improved text entry can reduce both input overhead and output overhead, which are the burden of providing inputs to and receiving outputs from the intermediate device, respectively. I introduce three computational methods for reducing input overhead and one for reducing output overhead. First, I show how input data mining can eliminate the need for user inputs altogether. Specifically, I develop a method for mining controller inputs to gain deep insights about a players playing style, their preferences, and the nature of video games that they are playing, all of which can be used to personalize their experience without any explicit input on their part. Next, I introduce gaze locking, a method for sensing eye contact from an image that allows people to interact with computers, devices, and other objects just by looking at them. Third, I introduce computationally optimized keyboard designs for touchscreen manual input that allow people to type on smartphones faster and with far fewer errors than currently possible. Last, I introduce the racing auditory display (RAD), an audio system that makes it possible for people who are blind to play the same types of racing games that sighted players can play, and with a similar speed and sense of control as sighted players. The RAD shows how we can reduce output overhead to provide user interface parity between people with and without disabilities. Together, I hope that these systems open the door to even more efforts in unmediated interaction, with the goal of making computers less like devices that we use and more like abilities or powers that we have.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8PK2019 |
| Date | January 2018 |
| Creators | Smith, Brian Anthony |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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