Internet video category recognition

Grant Schindler, Larry Zitnick, Matthew A. Brown
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引用次数: 35

Abstract

In this paper, we examine the problem of internet video categorization. Specifically, we explore the representation of a video as a ldquobag of wordsrdquo using various combinations of spatial and temporal descriptors. The descriptors incorporate both spatial and temporal gradients as well as optical flow information. We achieve state-of-the-art results on a standard human activity recognition database and demonstrate promising category recognition performance on two new databases of approximately 1000 and 1500 online user-submitted videos, which we will be making available to the community.
互联网视频分类识别
本文主要研究网络视频的分类问题。具体来说,我们通过使用空间和时间描述符的各种组合来探索视频作为单词包的表示。描述符包含空间和时间梯度以及光流信息。我们在一个标准的人类活动识别数据库上取得了最先进的结果,并在两个新数据库上展示了有希望的类别识别性能,这些数据库包含大约1000个和1500个在线用户提交的视频,我们将向社区提供这些视频。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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