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 "automatic vehicle tracking and recognition from aerial image sequences"):
  Abstract: This paper addresses the problem of automated vehicle tracking and recognition from aerial image sequences. Motivated by its successes in the existing literature focus on the use of linear appearance subspaces to describe multi-view object appearance and highlight the challenges involved in their application as a part of a practical system. A working solution which includes steps for data extraction and normalization is described. In experiments on real-world data the proposed methodology achieved promising results with a high correct recognition rate and few, meaningful errors (type II errors whereby genuinely similar targets are sometimes being confused with one another). Directions for future research and possible improvements of the proposed method are discussed.

Includes members:
  Member "groupwise registration of aerial images":
    also connected through other hyperedges:
      (none)
  Member "discriminative extended canonical correlation analysis for pattern set matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "achieving stable subspace clustering by post processing generic clustering results")
  Member "matching objects across the textured smooth continuum":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device")
  Member "contextually learnt detection of unusual motion based behaviour in crowded public spaces":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "track everything limiting prior knowledge in online multi object recognition")
  Member "multiple object tracking in cluttered and crowded public spaces":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "track everything limiting prior knowledge in online multi object recognition")

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)