计算机科学 ›› 2014, Vol. 41 ›› Issue (3): 297-301.
邱飞岳,金锋涛,王丽萍,张维泽
QIU Fei-yue,JIN Feng-tao,WANG Li-ping and ZHANG Wei-ze
摘要: 滑动窗口是形状匹配中的常用检测方法,可以检测图像中不同尺度不同位置的多个物体。检测效果采用检测率和误检率来衡量。在传统的滑动窗口检测方法中,通常基于经验选取滑动步长和图像缩放规模这两个参数值,来获得较高的检验率和较低的误检率。然而这是典型的两目标优化问题,传统方法未考虑决策者对检验率与误检率的不同偏好。根据实际情况,考虑到决策者的正偏好(高检验率与低误检率)及负偏好(低检验率和高误检率),引入双极偏好控制策略,提出基于双极偏好的多目标粒子群算法(BPMOPSO)的滑动窗口参数优化方法。通过Leeds Cows图像数据集上图像的检测实验结果表明,与传统算法相比,该算法显著改善了滑动窗口检测中的检验率和误检率,且大大提高了运行效率。
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