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 clever elimination strategy for efficient minimal solvers"
  Abstract: We present a new insight into the systematic generation of minimal solvers in computer vision, which leads to smaller and faster solvers. Many minimal problem formulations are coupled sets of linear and polynomial equations where image measurements enter the linear equations only. We show that it is useful to solve such systems by first eliminating all the unknowns that do not appear in the linear equations and then extending solutions to the rest of unknowns. This can be generalized to fully non-linear systems by linearization via lifting. We demonstrate that this approach leads to more efficient solvers in three problems of partially calibrated relative camera pose computation with unknown focal length and/or radial distortion. Our approach also generates new interesting constraints on the fundamental matrices of partially calibrated cameras, which were not known before.

Connected through hyperedge HE-1 (induced by source paper "pl _ 1 p point line minimal problems under partial visibility in three views"):
  with members:
    - "trifocal relative pose from lines at points and its efficient solution"
    - "plmp point line minimal problems in complete multi view visibility"
    - "neighbourhood consensus networks"
    - "five point fundamental matrix estimation for uncalibrated cameras"
    - "a minimal closed form solution for multi perspective pose estimation using points and lines"
    - "inloc indoor visual localization with dense matching and view synthesis"
    - "a minimal solution for two view focal length estimation using two affine correspondences"
    - "multiview differential geometry of curves"

Connected through hyperedge HE-2 (induced by source paper "minimal solvers for indoor uav positioning"):
  with members:
    - "radially distorted conjugate translations"
    - "a new solution to the relative orientation problem using only 3 points and the vertical direction"

Connected through hyperedge HE-3 (induced by source paper "plmp point line minimal problems in complete multi view visibility"):
  with members:
    - "trifocal relative pose from lines at points and its efficient solution"
    - "beyond gr obner bases basis selection for minimal solvers"
    - "neighbourhood consensus networks"
    - "five point fundamental matrix estimation for uncalibrated cameras"
    - "a minimal closed form solution for multi perspective pose estimation using points and lines"
    - "inloc indoor visual localization with dense matching and view synthesis"
    - "a minimal solution for two view focal length estimation using two affine correspondences"
    - "multiview differential geometry of curves"

Connected through hyperedge HE-4 (induced by source paper "homography from two orientation and scale covariant features"):
  with members:
    - "five point fundamental matrix estimation for uncalibrated cameras"
    - "a minimal solution for two view focal length estimation using two affine correspondences"
    - "radially distorted conjugate translations"
    - "graph cut ransac"
    - "mods fast and robust method for two view matching"

Connected through hyperedge HE-5 (induced by source paper "on the two view geometry of unsynchronized cameras"):
  with members:
    - "rolling shutter camera synchronization with sub millisecond accuracy"

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)