Active capture: integrating human-computer interaction and computer vision/audition to automate media capture
Active capture: integrating human-computer interaction and computer vision/audition to automate media capture
复制标题
主动捕捉：集成人机交互和计算机视觉/试听以自动化媒体捕捉
DOI：
10.1109/icme.2003.1221584
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Marc Davis
中科院分区：
文献类型：
--
作者：
Marc Davis
自 19 世纪摄影和电影发明以来，虽然媒体捕捉设备已经从机械设备发展到计算设备，但其底层的用户交互范式基本保持不变。当前的媒体捕获交互技术并没有利用计算来解决关键问题：捕获高质量媒体资产所需的技能；从捕获的资产中选择可用资产所需的努力；缺乏描述媒体资产内容和结构的元数据，无法检索和（重新）使用它们。我们描述了一种新的媒体捕获交互和处理范例，它将捕获重新定义为带有反馈的控制过程。通过将人机交互、计算机视觉和听觉集成到“主动捕捉”过程中，我们克服了当前媒体捕捉设备、算法和交互技术的局限性。主动捕捉利用媒体制作知识来实现导演和摄影的自动化，从而实现带注释的、高质量的、可重复使用的媒体资产的自动化制作。
While the devices for media capture have advanced from mechanical to computational since the invention of photography and motion pictures in the 19th century, their underlying user interaction paradigms have remained largely unchanged. Current interaction techniques for media capture do not leverage computation to solve key problems: the skill required to capture high quality media assets; the effort required to select useable assets from captured assets; and the lack of metadata describing the content and structure of media assets that could enable them to be retrieved and (re)used. We describe a new interaction and processing paradigm for media capture that redefines capture as a control process with feedback. By integrating human-computer interaction and computer vision and audition into an "active capture" process, we overcome the limitations of current media capture devices, algorithms, and interaction techniques. Active capture leverages media production knowledge to automate direction and cinematography and thus enables the automated production of annotated, high quality, reusable media assets.