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: "camera calibration from dynamic silhouettes using motion barcodes"
  Abstract: Computing the epipolar geometry between cameras with very different viewpoints is often problematic as matching points are hard to find. In these cases, it has been proposed to use information from dynamic objects in the scene for suggesting point and line correspondences. #R##N#We propose a speed up of about two orders of magnitude, as well as an increase in robustness and accuracy, to methods computing epipolar geometry from dynamic silhouettes. This improvement is based on a new temporal signature: motion barcode for lines. Motion barcode is a binary temporal sequence for lines, indicating for each frame the existence of at least one foreground pixel on that line. The motion barcodes of two corresponding epipolar lines are very similar, so the search for corresponding epipolar lines can be limited only to lines having similar barcodes. The use of motion barcodes leads to increased speed, accuracy, and robustness in computing the epipolar geometry.

Connected through hyperedge HE-1 (induced by source paper "probabilistic inference for camera calibration in light microscopy under circular motion"):
  with members:
    - "deepmvs learning multi view stereopsis"
    - "learning a multi view stereo machine"

Connected through hyperedge HE-2 (induced by source paper "two view constraints on the epipoles from few correspondences"):
  with members:
    - "epipolar geometry based on line similarity"
    - "fundamental matrices from moving objects using line motion barcodes"

Connected through hyperedge HE-3 (induced by source paper "an epipolar line from a single pixel"):
  with members:
    - "epipolar geometry based on line similarity"
    - "fundamental matrices from moving objects using line motion barcodes"
    - "event retrieval using motion barcodes"

Connected through hyperedge HE-4 (induced by source paper "camera calibration by global constraints on the motion of silhouettes"):
  with members:
    - "fundamental matrices from moving objects using line motion barcodes"
    - "event retrieval using motion barcodes"

Connected through hyperedge HE-5 (induced by source paper "fundamental matrices from moving objects using line motion barcodes"):
  with members:
    - "epipolar geometry from temporal signatures and dynamic silhouettes"
    - "event retrieval using motion barcodes"

Connected through hyperedge HE-6 (induced by source paper "epipolar geometry based on line similarity"):
  with members:
    - "event retrieval using motion barcodes"

Connected through hyperedge HE-7 (induced by source paper "two points fundamental matrix"):
  with members:
    - "event retrieval using motion barcodes"

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)