Region-based methods have become the state-of-art solution for monocular 6-DOF object pose tracking in recent years. However, two main challenges still remain: the robustness to heterogeneous configurations (both foreground and background), and the robustness to partial occlusions. In this paper, we propose a novel region-based monocular 3D object pose tracking method to tackle these problems. Firstly, we design a new strategy to define local regions, which is simple yet efficient in constructing discriminative local color histograms. Contrary to previous methods which define multiple circular regions around the object contour, we propose to define multiple overlapped, fan-shaped regions according to polar coordinates. This local region partitioning strategy produces much less number of local regions that need to be maintained and updated, while still being temporally consistent. Secondly, we propose to detect occluded pixels using edge distance and color cues. The proposed occlusion detection strategy is seamlessly integrated into the region-based pose optimization pipeline via a pixel-wise weight function, which significantly alleviates the interferences caused by partial occlusions. We demonstrate the effectiveness of the proposed two new strategies with a careful ablation study. Furthermore, we compare the performance of our method with the most recent state-of-art region-based methods in a recently released large dataset, in which the proposed method achieves competitive results with a higher average tracking success rate. Evaluations on two real-world datasets also show that our method is capable of handling realistic tracking scenarios.

中文翻译：

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通过时间一致的基于极地的局部分区，对物体进行基于遮挡感知的区域 3D 姿态跟踪。


近年来，基于区域的方法已成为单目六自由度物体姿态跟踪的最先进的解决方案。然而，仍然存在两个主要挑战：对异构配置（前景和背景）的鲁棒性，以及对部分遮挡的鲁棒性。在本文中，我们提出了一种新颖的基于区域的单目 3D 物体姿态跟踪方法来解决这些问题。首先，我们设计了一种新的策略来定义局部区域，该策略简单而有效地构建有区别的局部颜色直方图。与之前围绕对象轮廓定义多个圆形区域的方法相反，我们建议根据极坐标定义多个重叠的扇形区域。这种局部区域划分策略产生的需要维护和更新的局部区域数量要少得多，同时仍然保持时间一致。其次，我们建议使用边缘距离和颜色提示来检测被遮挡的像素。所提出的遮挡检测策略通过像素级权重函数无缝集成到基于区域的姿态优化管道中，这显着减轻了部分遮挡造成的干扰。我们通过仔细的消融研究证明了所提出的两种新策略的有效性。此外，我们在最近发布的大型数据集中将我们的方法与最新的基于区域的方法的性能进行了比较，其中所提出的方法以更高的平均跟踪成功率实现了有竞争力的结果。对两个现实世界数据集的评估也表明我们的方法能够处理现实的跟踪场景。