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 video database of human faces under near infra red illumination for human computer interaction applications"
  Abstract: Human Computer Interaction (HCI) is an evolving area of research for coherent communication between computers and human beings. Some of the important applications of HCI as reported in literature are face detection, face pose estimation, face tracking and eye gaze estimation. Development of algorithms for these applications is an active field of research. However, availability of standard database to validate such algorithms is insufficient. This paper discusses the creation of such a database created under Near Infra-Red (NIR) illumination. NIR illumination has gained its popularity for night mode applications since prolonged exposure to Infra-Red (IR) lighting may lead to many health issues. The database contains NIR videos of 60 subjects in different head orientations and with different facial expressions, facial occlusions and illumination variation. This new database can be a very valuable resource for development and evaluation of algorithms on face detection, eye detection, head tracking, eye gaze tracking etc. in NIR lighting.

Connected through hyperedge HE-1 (induced by source paper "image based eye gaze tracking and its applications"):
  with members:
    - "escaf pupil centre localization algorithm with candidate filtering"
    - "recognition of activities from eye gaze and egocentric video"
    - "labelled pupils in the wild a dataset for studying pupil detection in unconstrained environments"
    - "a framework for fast face and eye detection"
    - "else ellipse selection for robust pupil detection in real world environments"
    - "a drowsiness detection scheme based on fusion of voice and vision cues"
    - "appearance based gaze estimation in the wild"
    - "design and implementation of real time algorithms for eye tracking and perclos measurement for on board estimation of alertness of drivers"

Connected through hyperedge HE-2 (induced by source paper "specface a dataset of human faces wearing spectacles"):
  with members:
    - "a vision based system for monitoring the loss of attention in automotive drivers"
    - "automated alertness and emotion detection for empathic feedback during e learning"

Connected through hyperedge HE-3 (induced by source paper "a drowsiness detection scheme based on fusion of voice and vision cues"):
  with members:
    - "a vision based system for monitoring the loss of attention in automotive drivers"
    - "automated alertness and emotion detection for empathic feedback during e learning"

Connected through hyperedge HE-4 (induced by source paper "fast computation of perclos and saccadic ratio"):
  with members:
    - "a vision based system for monitoring the loss of attention in automotive drivers"

Connected through hyperedge HE-5 (induced by source paper "detection and estimation of iris centre"):
  with members:
    - "a vision based system for monitoring the loss of attention in automotive drivers"

Connected through hyperedge HE-6 (induced by source paper "an improved algorithm for eye corner detection"):
  with members:
    - "a vision based system for monitoring the loss of attention in automotive drivers"

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)