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 novel method for extrinsic calibration of a 2 d laser rangefinder and a camera"
  Abstract: We present a novel solution for extrinsically calibrating a camera and a Laser Rangefinder (LRF) by computing the transformation between the camera frame and the LRF frame. Our method is applicable for LRFs which measure only a single plane. It does not rely on observing the laser plane in the camera image. Instead, we show that point-to-plane constraints from a single observation of a V-shaped calibration pattern composed of two non-coplanar triangles suffice to uniquely constrain the transformation. Next, we present a method to obtain a solution using point-to-plane constraints from single or multiple observations. Along the way, we also show that previous solutions, in contrast to our method, have inherent ambiguities and therefore must rely on a good initial estimate. Real and synthetic experiments validate our method and show that it achieves better accuracy than previous methods.

Connected through hyperedge HE-1 (induced by source paper "automatic extrinsic calibration between a camera and a 3d lidar using 3d point and plane correspondences"):
  with members:
    - "automated evaluation of semantic segmentation robustness for autonomous driving"
    - "lidar camera calibration using 3d 3d point correspondences"

Connected through hyperedge HE-2 (induced by source paper "tree morphology for phenotyping from semantics based mapping in orchard environments"):
  with members:
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"
    - "a robotic vision system to measure tree traits"

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)