human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a metric on the space of finite sets of trajectories for evaluation of multi target tracking algorithms"):
  Abstract: In this paper, we propose a metric on the space of finite sets of trajectories for assessing multi-target tracking algorithms in a mathematically sound way. The metric can be used, e.g., to compare estimates from algorithms with the ground truth. It includes intuitive costs associated to localization, missed and false targets and track switches. The metric computation is based on multi-dimensional assignments, which is an NP hard problem. Therefore, we also propose a lower bound for the metric, which is also a metric for sets of trajectories and is computable in polynomial time using linear programming (LP). The LP metric can be implemented using alternating direction method of multipliers such that the complexity scales linearly with the length of the trajectories.

Includes members:
  Member "poisson multi bernoulli mixture filter direct derivation and implementation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vehicular multi object tracking with persistent detector failures")
  Member "generalized optimal sub pattern assignment metric":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking")
  Member "multiple target tracking based on sets of trajectories":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "trajectory phd and cphd filters")
  Member "a metric for sets of trajectories that is practical and mathematically consistent":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "track to reconstruct and reconstruct to track")
  Member "an efficient variational approximation of the best fitting multi bernoulli filter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CV(Computer Vision and Pattern Recognition)