中文摘要：

为解决复杂场景中的前景提取问题提出一种基于三维光场分析的静态场景前景分割方法．首先，通过在一条直线等间距的不同视点上拍摄场景的序列图像构建密集采样的三维光场．其次，用线段检测（LSD）直线检测算法从对极平面图（EPI）中分析提取出场景边缘及其深度信息．借助分段三次Hermite多项式（PCHIP）快速插值算法恢复整个场景的深度信息．最终，通过阈值法实现对不同深度的前景物体的分割．初步实验结果表明，本方法能够较准确地恢复场景中多个物体之间的空间关系，前景分割结果较好地克服了现有基于区域聚类和数学形态学等方法在复杂场景应用中存在的过分割问题．

英文摘要：

To address the problem of extracting foreground objects from complex scenes, a 3D light field based method for foreground segmentation of static scenes was presented. Firstly, the method relies on densely sampled 3D light field formed by stacking a sequence of images captured at different viewpoints. These viewpoints were equally spaced along a linear path so that object trace was smooth in epipolar plan image （EPI）. Secondly, line segment detection （LSD） method was performed to extract edges and compute the corresponding depth in EPI, based on which a depth map of the scene was obtained through a fast local depth interpolation algorithm. Piecewise cubic Hermite interpolating polynomial （PCI-IIP） algorithm proved to have desirable results in this phase. Finally, the recovered dense depth information was exploited to facilitate foreground segmentation. A threshold approach was used to separate different objects in scenes. Preliminary experimental resuits show that our method is able to estimate the correct relative spatial relation of multiple objects and our proposed foreground segmentation method reduces over-segmentation effects existed in traditional methods based on region clustering and mathematical morphology.