基于非齐次FRAME模型的感兴趣目标定位算法

传统的基于形状信息目标定位算法，对目标发生形变及其阻挡的情况下的检测存在较大的困难。为此，本文提出一种基于非齐次FRAME（Inhomogeneous Filters,Random filed, And Maximum Entropy,缩写IFRAME）模型的感兴趣目标检测算法，该模型由能在位置和方向进行局部扰动的基函数组成，是一种可变形模板，因此一定程度上提高定位算法在物体发生形变情况下的鲁棒性。经过多组实验结果表明，本文所提出的算法能较好地解决目标在发生形变、存在遮挡以及复杂背景下的定位问题。

Object Localization Algorithm Based on Inhomogeneous FRAME Model

Because the traditional object localization algorithm based on shape information is difficult to detect the object when the target is viewed from different angle or existing a little deformation. A localization algorithm of Object-of-Interest （OOI） based on inhomogeneous model to solve this problem is presented in this paper. Basis function that make up of the model can be adjusted by local perturbation to fit the image, so it is robust when target occurred a little deformation or the presence of occlusion. The experimental results show that our method can solve the problem of localization when the target is partly changed, occlusive or in complex background.