旋转矩形的快速积分与旋转Haar-Like特征在旋转物体检测中的应用

M. Oualla, Khalid Ounachad, A. Sadiq
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引用次数: 2

摘要

维奥拉和琼斯使用的积分图像技术通常用于计算输入图像中矩形滤波器的积分。这个过滤器是一个直线矩形。提出了一种基于brresenham分割算法的图像内任意旋转角度的图像积分方法。我们使用一些像素-称为关键点,形成旋转矩形的四个部分,来计算其积分图像。我们的方法侧重于三个基本任务;首先是确定一段的绘制规则(SDR),其次是识别矩形r的所有关键点,第三是计算积分图像。这种方法的速度取决于矩形的大小和旋转角度。为了证明我们的想法的有效性,我们将其应用于我们在后来的工作[12]中提出的旋转haar样特征,其目标是改进Viola和Jones算法以检测给定图像中的旋转面部。我们在更广泛的图像数据库上进行了测试,结果表明,将该技术应用于旋转Haar-Like特征,总体上提高了目标检测器的性能,尤其是人脸。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Fast Integration of a Rotated Rectangle Applied to the Rotated Haar-Like Features for Rotated Objects Detection
The Integral Image technique, used by Viola and Jones, is generally used to calculate the integral of a rectangular filter in an input picture. This filter is a rectilinear rectangle. We propose a method to integrate a rotated one by any angle of rotation inside an image based on the Bresenham algorithm of drawing a segment. We use some pixels – called key points that forms the four segments of a rotated rectangle, to calculate its Integral Image. Our method focuses on three essential tasks; the first is to determine the rule for drawing a segment (SDR), the second is to identify all the key points of the rectangle r, and the third is to calculate the integral image. The speed of this method depends on the size and angle of rotation of the rectangle. To demonstrate the efficiency of our idea, we applied it to the rotated Haar-like features that we proposed in a later work [12], which had as objectives the improvement of the Viola and Jones algorithm to detect the rotated faces in a given image. We performed tests on more widespread databases of images, which showed that the application of this technique to rotated Haar-Like features improves the performance of object detectors, in general, and faces in particular.
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