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 "comparative evaluation of action recognition methods via riemannian manifolds fisher vectors and gmms ideal and challenging conditions"):
  Abstract: We present a comparative evaluation of various techniques for action recognition while keeping as many variables as possible controlled. We employ two categories of Riemannian manifolds: symmetric positive definite matrices and linear subspaces. For both categories we use their corresponding nearest neighbour classifiers, kernels, and recent kernelised sparse representations. We compare against traditional action recognition techniques based on Gaussian mixture models and Fisher vectors (FVs). We evaluate these action recognition techniques under ideal conditions, as well as their sensitivity in more challenging conditions (variations in scale and translation). Despite recent advancements for handling manifolds, manifold based techniques obtain the lowest performance and their kernel representations are more unstable in the presence of challenging conditions. The FV approach obtains the highest accuracy under ideal conditions. Moreover, FV best deals with moderate scale and translation changes.

Includes members:
  Member "joint recognition and segmentation of actions via probabilistic integration of spatio temporal fisher vectors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "encoding the local connectivity patterns of fmri for cognitive state classification")
  Member "bags of affine subspaces for robust object tracking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "extrinsic methods for coding and dictionary learning on grassmann manifolds")
  Member "kernel methods on the riemannian manifold of symmetric positive definite matrices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "identity preserving face recovery from stylized portraits")
  Member "learning discriminative stein kernel for spd matrices and its applications":
    also connected through other hyperedges:
      (none)
  Member "multi action recognition via stochastic modelling of optical flow and gradients":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards miss universe automatic prediction the evening gown competition")
  Member "log euclidean bag of words for human action recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi camera action dataset for cross camera action recognition benchmarking")
  Member "random projections on manifolds of symmetric positive definite matrices for image classification":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "comparison among dimensionality reduction techniques based on random projection for cancer classification")
  Member "optimizing over radial kernels on compact manifolds":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sketch specific data augmentation for freehand sketch 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)