基于多级梯度能量描述的压缩域人脸检测

针对JPEG2000彩色图像，提出了一种结合肤色和纹理信息，直接在小波压缩域操作的人脸检测方法。该方法有3大特点:首先，提出了小波域人脸模式的多级梯度能量描述，在有效表征脸部特点的同时，可避免复杂的压缩域图像缩放操作，首次较好地解决了压缩域人脸检测中尺寸未知的难点；其次，优化YCbCr彩色空间肤色模型，提高肤色分割准确度；最后，在检测器的设计中，将基于规则的简单分类器和基于神经网络的复杂分类器有机结合，进一步加快处理速度。实验结果表明，提出的方法是有效而快速的。

Face Detection in Compressed Domain Based on Multi-level Gradient Energy Presentation

In this paper, a fast face detection algorithm for JPEG2000 color images is presented, which combines both color and texture information in order to find a good balance between speed and detection reliability. The algorithm is designed to work directly on the wavelet compressed domain which possesses the following characters: First of all, the multi-level gradient energy presentation of face pattern is proposed, which not only can highlight the facial parts in possible face patterns, but also can address effectively the problem of unknown size in face detection in compressed domain and therefore avoid the complex resolution transform in arbitrary ratios; secondly, the skin-color model in YChCr space is ameliorated to improve the reliability of skin segmentation; finally, a hierarchical detector which integrates the simply rule-based classifiers and complex neural network based classifier is designed to further improve the processing speed. Experimental results show that the proposed scheme is efficient and effective.