Handbook of Multimedia for Digital Entertainment and Arts
Handbook of Multimedia for Digital Entertainment and Arts
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数字娱乐和艺术多媒体手册
DOI：
10.1007/978-0-387-89024-1_12
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Zad D
中科院分区：
文献类型：
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作者：
Zad D
在本文中，我们专注于自制电影的元数据，如YouTube和Google Video上的电影，其持续时间随着上传限制的下降而增加。虽然简单的标签对于包含相对少量语义内容的传统非常短的视频片段的大多数目的可能已经足够了，但是对于体现更复杂语义的较长持续时间的电影，情况并非如此。创建元数据是一个耗时的过程，需要大量的个人努力，然而，这种努力可以大大减少利用Web 2.0社区的力量来创建，更新和维护it. Consequently，我们认为在Web 2.0环境中的电影注释，这样用户创建和共享元数据协作，并提出了一个架构协作电影注释。这种架构源于一个实证实验的结果，其中元数据创建工具，YouTube和MPEG-7建模工具，被用户用来创建电影元数据。下一节将讨论协作检索和标记领域的相关工作。然后，我们描述了50个用户的样本进行的实验。接下来，结果提供了一些洞察用户如何与现有的工具和系统进行交互，以注释电影。基于这些结果，本文然后开发了一个架构的协同电影注释。
In this paper, we focus on metadata for self-created movies like those found on YouTube and Google Video, the duration of which are increasing in line with falling upload restrictions. While simple tags may have been sufficient for most purposes for traditionally very short video footage that contains a relatively small amount of semantic content, this is not the case for movies of longer duration which embody more intricate semantics. Creating metadata is a time-consuming process that takes a great deal of individual effort; however, this effort can be greatly reduced by harnessing the power of Web 2.0 communities to create, update and maintain it. Consequently, we consider the annotation of movies within Web 2.0 environments, such that users create and share that metadata collaboratively and propose an architecture for collaborative movie annotation. This architecture arises from the results of an empirical experiment where metadata creation tools, YouTube and an MPEG-7 modelling tool, were used by users to create movie metadata. The next section discusses related work in the areas of collaborative retrieval and tagging. Then, we describe the experiments that were undertaken on a sample of 50 users. Next, the results are presented which provide some insight into how users interact with existing tools and systems for annotating movies. Based on these results, the paper then develops an architecture for collaborative movie annotation.