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Recently, Minimum Cost Multicut Formulations have been proposed and proven tobe successful in both motion trajectory segmentation and multi-target trackingscenarios. Both tasks benefit from decomposing a graphical model into anoptimal number of connected components based on attractive and repulsivepairwise terms. The two tasks are formulated on different levels of granularityand, accordingly, leverage mostly local information for motion segmentation andmostly high-level information for multi-target tracking. In this paper we arguethat point trajectories and their local relationships can contribute to thehigh-level task of multi-target tracking and also argue that high-level cuesfrom object detection and tracking are helpful to solve motion segmentation. Wepropose a joint graphical model for point trajectories and object detectionswhose Multicuts are solutions to motion segmentation {\it and} multi-targettracking problems at once. Results on the FBMS59 motion segmentation benchmarkas well as on pedestrian tracking sequences from the 2D MOT 2015 benchmarkdemonstrate the promise of this joint approach.

A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects