Research of Face Detection System Applied for Detecting Faces with Complex Background and Illumination

An effective face detection system used for detecting multi pose frontal face in gray images is presented. Image preprocessing approaches are applied to reduce the influence of the complex illumination. Eye-analog pairing and improved multiple related template matching are used to glancing and accurate face detecting, respectively. To shorten the time cost of detecting process, we employ prejudge rules in checking candidate image segments before template matching. Test by our own face database with complicated illumination and background, the system has high calculation speed and illumination independency, and obtains good experimental results.

A face detection algorithm based on high dimensional space geometry

In this paper, a face detection algorithm which is based on high dimensional space geometry has been proposed. Then after the simulation experiment of Euclidean Distance and the introduced algorithm, it was theoretically analyzed and discussed that the proposed algorithm has apparently advantage over the Euclidean Distance. Furthermore, in our experiments in color images, the proposed algorithm even gives more surprises.

An algorithm for removing facial makeup disturbances based on high dimensional imaginal geometry

In this paper, a novel algorithm for removing facial makeup disturbances as a face detection preprocess based on high dimensional imaginal geometry is proposed. After simulation and practical application experiments, the algorithm is theoretically analyzed. Its apparent effect of removing facial makeup and the advantages of face detection with this pre-process over face detection without it are discussed. Furthermore, in our experiments with color images, the proposed algorithm even gives some surprises.

基于人脸检测的自动摄像跟踪系统开发研究

自动摄像跟踪系统，是一种通过传感器检测或者数字图像处理的方法，控制摄像机自动的对运动中的人物或特定物体实施跟踪拍摄的系统，融合了计算机网络通信、计算机视觉、传感器网络等多个领域的技术，包含一系列软件和硬件设备，可以广泛运用在安全保卫视频监控，会议摄像，课堂和讲座摄像，表演摄像等场景，是近年来需求增长较大的领域。 人脸检测是数字图像处理和计算机视觉的一个分支问题，指的是在输入的图像中判断是否有人脸存在，并确定出所有人脸的位置、大小甚至姿势朝向的过程，作为进一步控制和处理的依据。这是计算机视觉方向最热门的技术专题之一，拥有非常广阔的应用空间。 目前还没有成熟的自动跟踪摄像系统应用于安全保卫或一般民用摄像领域，已有的一些类似系统也不能完全达到自动跟踪人物摄像的要求，性能距离全自动化无人干涉的跟踪摄像还有相当差距。 本文旨在运用计算机网络作为图像数据和控制信息媒体，运用数字图像处理领域计算机视觉中人脸检测和人脸跟踪的技术作为自动人物识别的依据，设计人物检测、人物跟踪、摄像机自动跟踪拍摄、人物位置运动估算、简单运动估计等算法策略，研究和开发一套完整的自动摄像跟踪系统软件，支持网络远程访问和控制，在无需人为操作和调整的情况下，实现对人物脸部自动跟踪拍摄的功能。这个系统适用于一般需求的安保视频监控和课堂自动摄像的应用。 本系统相对于已有的性能较好的类似系统——红外视频监控系统有许多明显优势，在达到很好的智能化、实时性、响应速度和准确性的同时，实现了设备的简化，大大降低了成本；同时在现场部署时不需要重新配置，后期维护简便；并且能够实现连续位置跟踪；系统稳定性优良等等。

人脸检测的一种混合方法研究

人脸检测作为自动人脸识别系统的第一个环节具有非常重要的作用,为了解决目前大部分人脸检测方法存在的分类器训练困难和检测计算量大等问题,提出了一种人脸检测的混合方法。该方法由两级分类器组成,第一级为粗分类器主要过滤大部分非人脸区域,第二级为核心分类器,在由第一级粗分类的基础上利用非线性SVM算法进行人脸检测。在CMU数据库上的实验结果表明,该方法具有较高的人脸检测率,检测速度得到大幅提高。

Visual-Context Boosting for Eye Detection

Eye detection plays an important role in many practical applications. This paper presents a novel two-step scheme for eye detection. The first step models an eye by a newly defined visual-context pattern (VCP), and the second step applies semisupervised boosting for precise detection. VCP describes both the space and appearance relations between an eye region (region of eye) and a reference region (region of reference). The context feature of a VCP is extracted by using the integral image. Aiming to reduce the human labeling efforts, we apply semisupervised boosting, which integrates the context feature and the Haar-like features for precise eye detection. Experimental results on several standard face data sets demonstrate that the proposed approach is effective, robust, and efficient. We finally show that this approach is ready for practical applications.