Huang Hong, Zhong Fan, Qin Xueying
IEEE Trans Vis Comput Graph. 2022 Dec;28(12):4319-4331. doi: 10.1109/TVCG.2021.3085197. Epub 2022 Oct 26.
Region-based methods are currently achieving state-of-the-art performance for monocular 3D object tracking. However, they are still prone to fail in cases of partial occlusions and ambiguous colors. We propose a novel region-based method to tackle these problems. The key idea is to derive a pixel-wise weighted region-based cost function using contour constraints. First, we propose a novel region-based cost function using search lines around the object contour, which is more efficient than previous region-based cost functions using signed distance transform, and in the meantime can deal with partial occlusions and ambiguous colors more effectively. Second, we propose an optimal searching strategy to search the object contour points in cluttered scenes, and then use the object contour points to detect partial occlusions and ambiguous colors. Third, we propose a pixel-wise weight function based on color and distance constraints of the object contour points, and integrate it into the proposed region-based cost function to reduce the negative impact of partial occlusions and ambiguous colors. We verify the effectiveness and efficiency of our method on challenging public datasets. Experiments demonstrate that our method outperforms the recent state-of-the-art region-based methods in complex scenarios, especially in the presence of partial occlusions and ambiguous colors.
基于区域的方法目前在单目3D目标跟踪方面取得了领先的性能。然而，在部分遮挡和颜色模糊的情况下，它们仍然容易失败。我们提出了一种新颖的基于区域的方法来解决这些问题。关键思想是使用轮廓约束来推导逐像素加权的基于区域的代价函数。首先，我们使用围绕物体轮廓的搜索线提出了一种新颖的基于区域的代价函数，它比以前使用符号距离变换的基于区域的代价函数更有效，同时可以更有效地处理部分遮挡和颜色模糊。其次，我们提出了一种最优搜索策略，用于在杂乱场景中搜索物体轮廓点，然后使用物体轮廓点来检测部分遮挡和颜色模糊。第三，我们基于物体轮廓点的颜色和距离约束提出了一个逐像素权重函数，并将其集成到所提出的基于区域的代价函数中，以减少部分遮挡和颜色模糊的负面影响。我们在具有挑战性的公共数据集上验证了我们方法的有效性和效率。实验表明，我们的方法在复杂场景中优于最近的基于区域的领先方法，特别是在存在部分遮挡和颜色模糊的情况下。
