Scalable Face Track Retrieval in Video Archives Using Bag-of-Faces Sparse Representation
Scalable Face Track Retrieval in Video Archives Using Bag-of-Faces Sparse Representation
复制标题
DOI：
10.1109/tcsvt.2016.2538520
复制
发表时间：
2017-07
影响因子：
8.4
通讯作者：
Bor-Chun Chen;Yan-Ying Chen;Y. Kuo;T. Ngo;Duy-Dinh Le;S. Satoh;Winston H. Hsu
中科院分区：
文献类型：
--
作者：
Bor-Chun Chen;Yan-Ying Chen;Y. Kuo;T. Ngo;Duy-Dinh Le;S. Satoh;Winston H. Hsu
庞大的视频档案，包括新闻节目、戏剧、电影和网络视频（例如，YouTube）在我们的日常生活中。在所有这些视频中，人通常是最重要的主题之一。使用最先进的技术，我们可以有效地检测和跟踪视频中的人脸。为了组织大规模的人脸轨迹，包含序列（检测）连续的人脸在视频中，我们提出了一种有效的方法来检索人脸轨迹使用袋的脸稀疏表示（BoF-SR）。使用所提出的方法，人脸轨迹被编码为一个单一的BoF-SR，因此允许一个有效的索引方法来处理大规模的数据。为了进一步考虑人脸轨迹中可能的变化，我们将我们的方法推广到以无监督的方式找到多个SR，以表示一袋人脸并平衡性能和检索时间之间的权衡。在两个真实世界（百万级）数据集上的实验结果证实，与不同的最先进的方法相比，所提出的方法实现了显着的性能增益。
Huge video archives consisting of news programs, dramas, movies, and Web videos (e.g., YouTube) are available in our daily life. In all these videos, human is usually one of the most important subjects. Using state-of-the-art techniques, we can efficiently detect and track faces in the videos. In order to organize large-scale face tracks, containing sequences of (detected) consecutive faces in the videos, we propose an efficient method to retrieve human face tracks using bag-of-faces sparse representation (BoF-SR). Using the proposed method, a face track is encoded as a single BoF-SR, therefore allowing an efficient indexing method to handle large-scale data. To further consider the possible variations in face tracks, we generalize our method to find multiple SRs, in an unsupervised manner, to represent a bag of faces and balance the tradeoff between performance and retrieval time. The experimental results on two real-world (million-scale) data sets confirm that the proposed methods achieve significant performance gains compared with different state-of-the-art methods.