PhD dissertation by Pei-Yu (Peggy) Chi, summer 2016
UC Berkeley Computer Science
This dissertation is available on my website [pdf, 17.4MB], or see the Berkeley EECS Technical Reports site.
When attempting to accomplish unfamiliar tasks, people often look for tutorials to follow instructions. While it is easy to access online instructions shared by domain experts, navigating step-by-step guidance using existing tools remains inefficient. In addition, producing high-quality instructions that are easy to follow requires authoring expertise and a significant time investment in editing. This dissertation introduces video-based recording, editing, and playback tools optimized for creating and consuming tutorials from author demonstrations. Our interactive systems capture videos and high-level events that are important to a learner. Using video and audio analysis techniques, we develop algorithms that automatically produce high-quality instructions, which dramatically reduce the effort required for amateur creators. By introducing novel tutorial formats combined with video content, these designs in turn improve viewers’ learning experience.
We present a series of authoring tools that enable amateur authors to create effective tutorials: 1) MixT is a system that automatically generates step-by-step mixed media tutorials from software demonstrations. 2) DemoWiz is a tool that provides an increased awareness of upcoming events in a software demonstration video. 3) DemoCut is a semi-automatic video editing tool for physical tasks. 4) Kinectograph is a recording device that automatically follows an instructor for filming a physical demonstration. 5) DemoDraw is a multi-modal system to generate step-by-step motion illustrations from author’s body movements. Current authoring practices from professionals are encoded into automatic algorithms and interactive techniques. These systems are evaluated through a series of studies, which demonstrate that users can efficiently create and follow concise instructions using our tools.
Pei-Yu (Peggy) Chi received her M.S. from the MIT Media Lab and her M.S. in Computer Science and B.B.A. in Information Management from National Taiwan University. She develops interactive systems that support users' creativity and learning activities. Her research has received a Best Paper Award at ACM CHI, a Google PhD Fellowship in Human-Computer Interaction, a Berkeley Fellowship for Graduate Study, and a MIT Media Lab Fellowship with ITRI.
After five years of study in Computer Science at UC Berkeley, Peggy received the Doctor of Philosophy degree in August 2016. She will join Google Inc. as a research scientist in Mountain View, California.
- Introduction
- Background
- Related Work
- MixT
- DemoWiz
- DemoCut
- Kinectograph
- DemoDraw
- Conclusion
- Appendices
- Dissertation Writing and Filing | Berkeley Graduate Division
- Ph.D. Student Guide | EECS at UC Berkeley
- EECS Graduation Checklist
- Graduate Handbook | EECS at UC Berkeley
- Signature page
- Permission (to include previously published or co-authored material)
- Evaluation form
- Dissertation talk form
- Email permissions for figure reuse
BibTeX citation:
@phdthesis{Chi:EECS-2016-150,
Author = {Chi, Pei-Yu},
Title = {Designing Video-Based Interactive Instructions},
School = {EECS Department, University of California, Berkeley},
Year = {2016},
Month = {Aug},
URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-150.html},
Number = {UCB/EECS-2016-150}
}
EndNote citation:
%0 Thesis
%A Chi, Pei-Yu
%T Designing Video-Based Interactive Instructions
%I EECS Department, University of California, Berkeley
%D 2016
%8 August 15
%@ UCB/EECS-2016-150
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-150.html
%F Chi:EECS-2016-150