基于Web图像数据集的视频新闻人脸检索

Marco Leo, F. Battisti, M. Carli, A. Neri
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引用次数: 1

摘要

广播新闻节目的自动标注是多媒体新闻评论的一个具有挑战性的课题。通常在视频流中,人的头部会持续移动,面部表情、光照条件和摄像机运动的变化会对图像外观产生显著的扭曲,从而在很大程度上影响识别性能。本文提出了一种电视广播节目人脸自动识别系统。该方法是基于尺度不变特征变换描述子和基于特征面的方法的联合使用。该算法已在两个国家广播频道上进行了测试。实验结果表明,这两种方法的联合使用提高了识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Video news face retrieval based on Web image datasets
Automatic annotation of broadcasting news programs is a challenging task for multimedia press review. Usually in a video stream, the head of a person moves continuously and changes in facial expressions, lighting conditions, and camera motion produce significant distortions in the image appearance that can largely affect recognition performances. In this paper a system for automatic face identification in TV broadcasting programs is proposed. The proposed approach is based on a joint use of Scale Invariant Feature Transform descriptor and Eigenfaces-based approach. The algorithm has been tested on two national broadcasting channels. Experimental results show that the joint use of these two approaches improves the recognition rate.
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