人脸检测与跟踪是一个重要而活跃的研究领域，它在视频监控、生物特征识别、视频编码等领域有着广泛的应用前景。该项目的目标是在FPGA板上实现实时系统来检测和跟踪人脸。人脸检测算法包括肤色分割和图像滤波。通过计算被检测区域的质心来确定人脸的位置。该算法的软件版本独立实现，并在matlab的静止图像上进行测试。虽然从MATLAB到Verilog的转换没有预期的那样顺利，实验结果证明了实时系统的准确性和有效性，甚至在不同的光线、面部姿态和肤色的条件下也是如此。所有硬件实现的计算都是以最小的计算量实时完成的，因此适合于功率受限的应用。(Face detection and tracking is an important and active research field, and it has a wide range of applications in video surveillance, biometrics, video coding and other fields. The goal of the project is to implement real-time systems on the FPGA board to detect and track faces. Face detection algorithms include skin segmentation and image filtering. The location of the human face is determined by calculating the centroid of the detected region. The software version of the algorithm is implemented independently and tested on MATLAB still images. Although the conversion from MATLAB to Verilog is not as smooth as expected, the experimental results demonstrate the accuracy and effectiveness of real-time systems, even in different light, facial gestures and color conditions. All hardware implementations are performed in real-time with minimal computational complexity and are therefore suitable for power constrained applications.)