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 "globally consistent multi people tracking using motion patterns"):
  Abstract: Many state-of-the-art approaches to people tracking rely on detecting them in each frame independently, grouping detections into short but reliable trajectory segments, and then further grouping them into full trajectories. This grouping typically relies on imposing local smoothness constraints but almost never on enforcing more global constraints on the trajectories. In this paper, we propose an approach to imposing global consistency by first inferring behavioral patterns from the ground truth and then using them to guide the tracking algorithm. When used in conjunction with several state-of-the-art algorithms, this further increases their already good performance. Furthermore, we propose an unsupervised scheme that yields almost similar improvements without the need for ground truth.

Includes members:
  Member "mot16 a benchmark for multi object tracking":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stem seg spatio temporal embeddings for instance segmentation in videos")
  Member "simple online and realtime tracking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi object tracking via end to end tracklet searching and ranking")
  Member "online multi target tracking using recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multiple object tracking by flowing and fusing")
  Member "a multi cut formulation for joint segmentation and tracking of multiple objects":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "looking glamorous vehicle re id in heterogeneous cameras networks with global and local attention")
  Member "performance measures and a data set for multi target multi camera tracking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "weakly supervised discriminative feature learning with state information for person identification")
  Member "a metric for sets of trajectories that is practical and mathematically consistent":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "track to reconstruct and reconstruct to track")
  Member "plug and play cnn for crowd motion analysis an application in abnormal event detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning a distance function with a siamese network to localize anomalies in videos")
  Member "understanding trajectory behavior a motion pattern approach":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "understanding people flow in transportation hubs")

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)