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首页> 外文会议>Conference on Image Extraction, Segmentation, and Recognition Oct 22-24, 2001, Wuhan, China >Fast Hierarchical Knowledge-based Approach for Human Face Detection in Color Images
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Fast Hierarchical Knowledge-based Approach for Human Face Detection in Color Images

机译：基于快速分层知识的彩色图像人脸检测方法

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摘要

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc..
机译：本文提出了一种基于分层知识的快速方法，用于自动检测静止彩色图像中的多尺度直立人脸。该方法包括三个级别。在最高级别上，皮肤样区域由皮肤模型确定，该模型基于HSV颜色空间中的颜色属性色相和饱和度，以及归一化颜色空间中的红色和绿色属性。在第2级中，设计了一种新的眼睛模型以在分段的类似皮肤区域中选择人脸候选对象。眼睛模型的一个重要特征是它与人脸的大小无关。因此，仅用一次扫描图像就可以发现不同比例的人脸，从而大大减少了人脸检测的计算时间。在级别3中，应用与人脸的物理结构特征相一致的人脸马赛克图像模型来判断在人脸候选区域中是否存在人脸检测。该模型包括边缘规则和灰色规则。实验结果表明，该方法具有较高的鲁棒性和较高的速度。在人机交互和可视电话等方面具有广泛的应用前景。

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