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Multi-view Face Detection in Video

机译:视频中的多视角人脸检测

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摘要

A multi-view face detection method in video is proposed in this paper. The method is capable of locating human faces over a broad range of views in videos with complex scenes. Firstly, an improved frame difference is used to acquire promising regions of the image. Then it uses the presence of skin-tone pixels to locate faces. Finally, shape, edge pattern and facespecific features are used to verify the candidate face regions. The experimental results show that the proposed algorithm has high speed and low errordetection rate, so it can be used in the real-time video surveillance system. The main distinguishing contribution of this work is being able to detect faces irrespective of their poses, including frontal-view and side-view, whereas contemporary systems deal with frontal-view faces only. The other novel aspects of the work lie in its accuracy of acquiring the candidate area to segment objects from background with the help of motion information and skin information.
机译:提出了一种视频多视角人脸检测方法。该方法能够在具有复杂场景的视频中的广泛视图中定位人脸。首先,改进的帧差用于获取图像的有希望的区域。然后,它使用肤色像素的存在来定位脸部。最后,使用形状,边缘图案和特定于脸部的特征来验证候选脸部区域。实验结果表明,该算法具有较高的速度和较低的错误检测率,可用于实时视频监控系统。这项工作的主要区别在于能够检测到无论脸部姿势如何的人脸,包括正视图和侧视图,而现代系统仅处理正视图的脸。这项工作的其他新颖之处在于其在运动信息和皮肤信息的帮助下获取候选区域以将对象从背景中分割出来的准确性。

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