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.
翻译:视频说明是计算机科学和社会科学中的一个重要过程。许多视频说明工具(VATs)提供了广泛的特征,使得说明成为可能。我们广泛调查了超过59种增值税,并采访了跨学科研究人员,以评估增值税的可用性。我们的研究结果表明,大多数现有的增值税都具有压倒性用户界面、不良的互动技术和难以理解的特点。这往往导致说明时间延长、标签不一致和用户疲劳。我们引入了FEVA,这是一个带有简化互动技术的视频说明工具和一个动态界面,使标签工作容易和快速。FEVA侧重于速度、准确性和简便性,以便快速、一致和直截了当地作出说明。例如,说明员可以控制视频的速度和方向,用单一关键媒体标示开始和抵消标签。在我们用户研究中,FEVA用户平均需要比最受欢迎的说明工具(Advene、ANVIL、EVA、VIA、VIA和VIAN)少36%的互动。在智能/REVA中,参与者的级别和需求更低。