Correcting rolling-shutter distortion of CMOS sensors using facial feature detection
Correcting rolling-shutter distortion of CMOS sensors using facial feature detection
复制标题
使用面部特征检测校正 CMOS 传感器的卷帘快门失真
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
T. Boult
中科院分区：
文献类型：
--
作者：
B. Heflin;W. Scheirer;T. Boult
本文提出了一种基于人脸特征检测的全自动图像后处理方案，以校正水平时间剪切或滚动快门失真。当从具有滚动快门的CMOS相机获取图像或视频序列时，只要在图像帧的积分时间期间传感器和被成像物体之间存在相对水平移动，就会发生这种失真。与CCD传感器不同，例如行间CCD，它提供了一种称为全局快门的电子快门机制，其中所有像素的光收集在完全相同的时间开始和结束，CMOS传感器不能同时保存和存储所有像素。每个扫描线都按顺序曝光、采样和存储，导致图像的卷帘快门效应或时间失真，这将导致不准确的面部识别结果。人脸特征检测使用基于相关性的方法进行，具有低计算复杂度。然后使用关键面部特征点的位置来计算图像的时间水平剪切或失真。然后，该信息可以用于从检测到的面部或整个图像中去除时间水平剪切失真。我们目前的实验结果控制数据集和真实的场景显示，所提出的方法在扭转由CMOS卷帘快门传感器引起的时间水平剪切产生优异的结果，并显着提高了我们的面部识别算法的准确性。
This paper proposes a fully automated post image processing scheme based on facial feature detection to correct the horizontal temporal shear or rolling shutter distortion. This distortion occurs when obtaining images or video sequences from a CMOS camera with a rolling shutter whenever there is relative horizontal movement between the sensor and the object being imaged during the integration time of the image frame. Unlike CCD sensors, such as the interline CCD, which provides an electronic shutter mechanism called a global shutter in which the light collection starts and ends at exactly the same time for all pixels, CMOS sensors can not hold and store all the pixels at the same time. Each scanline is exposed, sampled, and stored in sequence, resulting in the rolling shutter effect or temporal distortion of the image that will cause inaccurate facial recognition results. Facial feature detection is performed using correlation based methods with low computational complexity. The location of key facial feature points is then used to calculate the temporal horizontal shear or the distortion of the image. This information can then be used to remove the temporal horizontal shear distortion from the detected face or the entire image. We present experimental results on controlled data sets and real scenes to show that the proposed method yields excellent results in reversing the temporal horizontal shear caused by the CMOS rolling shutter sensor and significantly improves the accuracy of our facial recognition algorithm.