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 "algebraic characterization of essential matrices and their averaging in multiview settings"):
  Abstract: Essential matrix averaging, i.e., the task of recovering camera locations and orientations in calibrated, multiview settings, is a first step in global approaches to Euclidean structure from motion. A common approach to essential matrix averaging is to separately solve for camera orientations and subsequently for camera positions. This paper presents a novel approach that solves simultaneously for both camera orientations and positions. We offer a complete characterization of the algebraic conditions that enable a unique Euclidean reconstruction of $n$ cameras from a collection of $(^n_2)$ essential matrices. We next use these conditions to formulate essential matrix averaging as a constrained optimization problem, allowing us to recover a consistent set of essential matrices given a (possibly partial) set of measured essential matrices computed independently for pairs of images. We finally use the recovered essential matrices to determine the global positions and orientations of the $n$ cameras. We test our method on common SfM datasets, demonstrating high accuracy while maintaining efficiency and robustness, compared to existing methods.

Includes members:
  Member "resultant based incremental recovery of camera pose from pairwise matches":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "video object segmentation based visual servo control and object depth estimation on a mobile robot platform")
  Member "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "averaging essential and fundamental matrices in collinear camera settings")
  Member "rotation averaging and strong duality":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the distribution of minima in intrinsic metric rotation averaging")
  Member "a new rank constraint on multi view fundamental matrices and its application to camera location recovery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "averaging essential and fundamental matrices in collinear camera settings")
  Member "shapefit and shapekick for robust scalable structure from motion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "baseline desensitizing in translation averaging")
  Member "linear global translation estimation with feature tracks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "averaging essential and fundamental matrices in collinear camera settings")
  Member "robust camera location estimation by convex programming":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning transformation synchronization")

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)