Handling object interaction is a fundamental challenge in practical multi-object tracking, even for simple interactive effects such as one object temporarily occluding another. We formalize the problem of occlusion in tracking with two different abstractions. In object-wise occlusion, objects that are occluded by other objects do not generate measurements. In measurement-wise occlusion, a previously unstudied approach, all objects may generate measurements but some measurements may be occluded by others. While the relative validity of each abstraction depends on the situation and sensor, measurement-wise occlusion fits into probabilistic multi-object tracking algorithms with much looser assumptions on object interaction. Its value is demonstrated by showing that it naturally derives a popular approximation for lidar tracking, and by an example of visual tracking in image space.
翻译:实际的多物体跟踪中,即使对于简单的交互效果,例如一个物体暂时取代另一个物体,处理对象的相互作用也是一项基本挑战。我们用两种不同的抽象跟踪将隔离问题正式确定下来。在对象角度的隔离中,由其他物体隐蔽的物体不会产生测量结果。在测量角度的隔离中,一个以前未经研究的方法,所有物体都可能产生测量结果,但有些测量结果可能为其他物体所隐蔽。虽然每个抽象的相对有效性取决于状况和感应器,但测量角度的隔离则适用于概率性多物体跟踪算法,在物体互动上假设的假设范围要大得多。其价值表现在显示它自然产生热点跟踪的近似值,以及在图像空间进行视觉跟踪的例子。