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: "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
  Abstract: Accurate estimation of camera matrices is an important step in structure from motion algorithms. In this paper we introduce a novel rank constraint on collections of fundamental matrices in multi-view settings. We show that in general, with the selection of proper scale factors, a matrix formed by stacking fundamental matrices between pairs of images has rank 6. Moreover, this matrix forms the symmetric part of a rank 3 matrix whose factors relate directly to the corresponding camera matrices. We use this new characterization to produce better estimations of fundamental matrices by optimizing an L1-cost function using Iterative Re-weighted Least Squares and Alternate Direction Method of Multiplier. We further show that this procedure can improve the recovery of camera locations, particularly in multi-view settings in which fewer images are available.

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"
    - "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"
    - "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"
    - "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"
    - "rotation averaging and strong duality"
    - "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"
    - "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"
    - "on some properties of calibrated trifocal tensors"

Connected through hyperedge HE-4 (induced by source paper "baseline desensitizing in translation averaging"):
  with members:
    - "shapefit and shapekick for robust scalable structure from motion"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-5 (induced by source paper "an overview of robust subspace recovery"):
  with members:
    - "fast robust and non convex subspace recovery"
    - "static and dynamic robust pca via low rank sparse matrix decomposition a review"
    - "on the complexity of robust pca and l1 norm low rank matrix approximation"
    - "estimation of camera locations in highly corrupted scenarios all about that base no shape trouble"
    - "static and dynamic robust pca and matrix completion a review"
    - "being robust in high dimensions can be practical"
    - "a well tempered landscape for non convex robust subspace recovery"
    - "coherence pursuit fast simple and robust principal component analysis"

Connected through hyperedge HE-6 (induced by source paper "exact camera location recovery by least unsquared deviations"):
  with members:
    - "baseline desensitizing in translation averaging"
    - "estimation of camera locations in highly corrupted scenarios all about that base no shape trouble"
    - "a survey of structure from motion"
    - "shapefit and shapekick for robust scalable structure from motion"
    - "shapefit exact location recovery from corrupted pairwise directions"
    - "robust computation of linear models by convex relaxation"
    - "robust camera location estimation by convex programming"
    - "stable camera motion estimation using convex programming"

Connected through hyperedge HE-7 (induced by source paper "estimation of camera locations in highly corrupted scenarios all about that base no shape trouble"):
  with members:
    - "exact camera location recovery by least unsquared deviations"
    - "a survey of structure from motion"
    - "shapefit and shapekick for robust scalable structure from motion"
    - "shapefit exact location recovery from corrupted pairwise directions"
    - "robust camera location estimation by convex programming"
    - "stable camera motion estimation using convex programming"

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)