human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"
  Abstract: This paper addresses the problem of recovering projective camera matrices from collections of fundamental matrices in multiview settings. We make two main contributions. First, given ${n \choose 2}$ fundamental matrices computed for $n$ images, we provide a complete algebraic characterization in the form of conditions that are both necessary and sufficient to enabling the recovery of camera matrices. These conditions are based on arranging the fundamental matrices as blocks in a single matrix, called the $n$-view fundamental matrix, and characterizing this matrix in terms of the signs of its eigenvalues and rank structures. Secondly, we propose a concrete algorithm for projective structure-from-motion that utilizes this characterization. Given a complete or partial collection of measured fundamental matrices, our method seeks camera matrices that minimize a global algebraic error for the measured fundamental matrices. In contrast to existing methods, our optimization, without any initialization, produces a consistent set of fundamental matrices that corresponds to a unique set of cameras (up to a choice of projective frame). Our experiments indicate that our method achieves state of the art performance in both accuracy and running time.

Connected through hyperedge HE-1 (induced by source paper "averaging essential and fundamental matrices in collinear camera settings"):
  with members:
    - "resultant based incremental recovery of camera pose from pairwise matches"
    - "algebraic characterization of essential matrices and their averaging in multiview settings"
    - "on the solvability of viewing graphs"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "linear global translation estimation with feature tracks"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-2 (induced by source paper "algebraic characterization of essential matrices and their averaging in multiview settings"):
  with members:
    - "resultant based incremental recovery of camera pose from pairwise matches"
    - "rotation averaging and strong duality"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "shapefit and shapekick for robust scalable structure from motion"
    - "linear global translation estimation with feature tracks"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-3 (induced by source paper "necessary and sufficient polynomial constraints on compatible triplets of essential matrices"):
  with members:
    - "algebraic characterization of essential matrices and their averaging in multiview settings"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "on some properties of calibrated trifocal tensors"

Question: Please tell me which class the center node 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)