# Multiple People Tracking by Lifted Multicut and Person Re-identification

## CVPR2017, MOTS

Posted by pshow on June 30, 2020

## Multiple People Tracking by Lifted Multicut and Person Re-identification

### 主要贡献

• we propose a novel graph based formulation that links and clusters person hypotheses over time by solving an instance of a minimum cost lifted multicut problem.
• ReID模型包含了外观与姿势特征。
• propose to cast multi-person tracking as the minimum cost lifted multicut problem. We introduce two types of edges (regular and lifted edges) for the tracking graph.

### 简介

similar looking people are considered as the same person only if they are connected by at least one feasible track (possibly skipping occlusion)

• 追踪目标的个数没有理论定义上的限制或者偏重。
• 由于同一帧中同一个目标的重复检测会被自然的聚类在一起，所以可以取消掉启发式的NMS算法

In order to avoid that distinct but similar looking people are assigned to the same track, a distinction must be made between the edges that define possible connections (i.e., a feasible set) and the edges that define the costs or rewards for assigning the incident nodes to distinct tracks (i.e., an objective function).

### 模型

Parameters.

lifted edges 提升边链接时间距离较远的相似目标。

Feasible Set.

Objective function.

Optimization.