Hanyang University, Seoul.
IEEE Trans Vis Comput Graph. 2014 Jan;20(1):99-110. doi: 10.1109/TVCG.2013.94.
Edge-based tracking is a fast and plausible approach for textureless 3D object tracking, but its robustness is still very challenging in highly cluttered backgrounds due to numerous local minima. To overcome this problem, we propose a novel method for fast and robust textureless 3D object tracking in highly cluttered backgrounds. The proposed method is based on optimal local searching of 3D-2D correspondences between a known 3D object model and 2D scene edges in an image with heavy background clutter. In our searching scheme, searching regions are partitioned into three levels (interior, contour, and exterior) with respect to the previous object region, and confident searching directions are determined by evaluating candidates of correspondences on their region levels; thus, the correspondences are searched among likely candidates in only the confident directions instead of searching through all candidates. To ensure the confident searching direction, we also adopt the region appearance, which is efficiently modeled on a newly defined local space (called a searching bundle). Experimental results and performance evaluations demonstrate that our method fully supports fast and robust textureless 3D object tracking even in highly cluttered backgrounds.
基于边缘的跟踪是一种快速且合理的无纹理 3D 目标跟踪方法，但是由于存在大量局部最小值，其在高度杂乱的背景中的鲁棒性仍然极具挑战性。为了解决这个问题，我们提出了一种新颖的方法，用于在高度杂乱的背景中快速而稳健地进行无纹理 3D 目标跟踪。所提出的方法基于在具有大量背景杂波的图像中，已知的 3D 对象模型和 2D 场景边缘之间的 3D-2D 对应关系的最优局部搜索。在我们的搜索方案中，搜索区域根据先前的对象区域划分为三个级别（内部、轮廓和外部），并且通过评估对应关系在其区域级别上的候选者来确定置信的搜索方向；因此，仅在置信的方向上而不是在所有候选者中搜索对应关系。为了确保置信的搜索方向，我们还采用了区域外观，该外观在新定义的局部空间（称为搜索束）上进行了有效建模。实验结果和性能评估表明，即使在高度杂乱的背景中，我们的方法也完全支持快速而稳健的无纹理 3D 目标跟踪。
