Abstract
We present a novel object tracking scheme that can track rigid objects in real time. The approach uses subpixel-precise image edges to track objects with high accuracy. It can determine the object position, scale, and rotation with subpixel-precision at around 80fps. The tracker returns a reliable score for each frame and is capable of self diagnosing a tracking failure. Furthermore, the choice of the similarity measure makes the approach inherently robust against occlusion, clutter, and nonlinear illumination changes. We evaluate the method on sequences from rigid objects from the OTB-2015 and VOT2016 dataset and discuss its performance. The evaluation shows that the tracker is more accurate than state-of-the-art real-time trackers while being equally robust.
Abstract (translated)
我们提出了一种新的物体跟踪方案,可以实时跟踪刚性物体。该方法使用亚像素精确图像边缘以高精度跟踪对象。它可以确定物体位置,比例和旋转,子像素精度约为80fps。跟踪器为每个帧返回可靠的分数,并且能够自我诊断跟踪失败。此外,相似性度量的选择使得该方法对于遮挡,杂波和非线性照明变化具有固有的鲁棒性。我们评估来自OTB-2015和VOT2016数据集的刚性对象的序列方法,并讨论其性能。评估表明,跟踪器比最先进的实时跟踪器更准确,同时具有同样强大的功能。
URL
https://arxiv.org/abs/1807.01952