论文标题
在多个对象跟踪中使用应用程序的脱节路径
Lifted Disjoint Paths with Application in Multiple Object Tracking
论文作者
论文摘要
我们提出了一个分离路径问题的扩展名，其中引入了其他\ emph {升起}边缘以提供路径连接性先验。我们称结果优化问题为提升的不相交路径问题。我们表明，由于整数多商品流量和3-SAT的降低，这个问题是NP-HARD。为了实现实际的全球优化，我们提出了几类线性不平等的类别，以产生高质量的LP - 放射率。此外，我们提出了有效的切割平面算法，以分离提出的线性不平等。提起的脱节路径问题是用于多个对象跟踪的自然模型，并允许用于远程时间相互作用的优雅数学公式。提起的边缘有助于防止ID开关并重新识别人员。我们提起的脱节路径跟踪器就输入检测实现了几乎最佳的分配。结果，它以MOT挑战的所有三个主要基准领先，在最先进的情况下有了显着改善。
We present an extension to the disjoint paths problem in which additional \emph{lifted} edges are introduced to provide path connectivity priors. We call the resulting optimization problem the lifted disjoint paths problem. We show that this problem is NP-hard by reduction from integer multicommodity flow and 3-SAT. To enable practical global optimization, we propose several classes of linear inequalities that produce a high-quality LP-relaxation. Additionally, we propose efficient cutting plane algorithms for separating the proposed linear inequalities. The lifted disjoint path problem is a natural model for multiple object tracking and allows an elegant mathematical formulation for long range temporal interactions. Lifted edges help to prevent id switches and to re-identify persons. Our lifted disjoint paths tracker achieves nearly optimal assignments with respect to input detections. As a consequence, it leads on all three main benchmarks of the MOT challenge, improving significantly over state-of-the-art.
