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 "batch based monocular slam for egocentric videos"):
  Abstract: Simultaneous Localization and Mapping (SLAM) from a monocular camera has been a well researched area. However, estimating camera pose and 3d geometry reliably for egocentric videos still remain a challenge. Some of the common causes of failures are dominant 3D rotations and low parallax between successive frames, resulting in unreliable pose and 3d estimates. For forward moving cameras, with no opportunities for loop closures, the drift leads to eventual failures for traditional feature based and direct SLAM techniques. We propose a novel batch mode structure from motion based technique for robust SLAM in such scenarios. In contrast to most of the existing techniques, we process frames in short batches, wherein we exploit short loop closures arising out of to-and-fro motion of wearer's head, and stabilize the egomotion estimates by 2D batch mode techniques such as motion averaging on pairwise epipolar results. Once pose estimates are obtained reliably over a batch, we refine the 3d estimate by triangulation and batch mode Bundle Adjustment (BA). Finally, we merge the batches using 3D correspondences and carry out a BA refinement post merging. We present both qualitative and quantitative comparison of our method on various public first and third person video datasets, to establish the robustness and accuracy of our algorithm over the state of the art.

Includes members:
  Member "computing egomotion with local loop closures for egocentric videos":
    also connected through other hyperedges:
      (none)
  Member "compact cnn for indexing egocentric videos":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "h o unified egocentric recognition of 3d hand object poses and interactions")
  Member "egosampling fast forward and stereo for egocentric videos":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "personalizing fast forward videos based on visual and textual features from social network")
  Member "hierarchical structure and motion recovery from uncalibrated images":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph based parallel large scale structure from motion")
  Member "predicting daily activities from egocentric images using deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "batch based activity recognition from egocentric photo streams revisited")
  Member "orb slam a versatile and accurate monocular slam system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")
  Member "robust camera location estimation by convex programming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)