  Video Annotation is a crucial process in computer science and social science
alike. Many video annotation tools (VATs) offer a wide range of features for
making annotation possible. We conducted an extensive survey of over 59 VATs
and interviewed interdisciplinary researchers to evaluate the usability of
VATs. Our findings suggest that most current VATs have overwhelming user
interfaces, poor interaction techniques, and difficult-to-understand features.
These often lead to longer annotation time, label inconsistencies, and user
fatigue. We introduce FEVA, a video annotation tool with streamlined
interaction techniques and a dynamic interface that makes labeling tasks easy
and fast. FEVA focuses on speed, accuracy, and simplicity to make annotation
quick, consistent, and straightforward. For example, annotators can control the
speed and direction of the video and mark the onset and the offset of a label
in real time with single key presses. In our user study, FEVA users, on
average, require 36% less interaction than the most popular annotation tools
(Advene, ANVIL, ELAN, VIA, and VIAN). The participants (N=32) rated FEVA as
more intuitive and required less mental demand. The code and demo are available
at http://www.snehesh.com/feva.
