human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Tracking People on a Torus"
  Abstract: We present a framework for monocular 3D kinematic pose tracking and viewpoint estimation of periodic and quasi-periodic human motions from an uncalibrated camera. The approach we introduce here is based on learning both the visual observation manifold and the kinematic manifold of the motion using a joint representation. We show that the visual manifold of the observed shape of a human performing a periodic motion, observed from different viewpoints, is topologically equivalent to a torus manifold. The approach we introduce here is based on the supervised learning of both the visual and kinematic manifolds. Instead of learning an embedding of the manifold, we learn the geometric deformation between an ideal manifold (conceptual equivalent topological structure) and a twisted version of the manifold (the data). Experimental results show accurate estimation of the 3D body posture and the viewpoint from a single uncalibrated camera.

Connected through hyperedge HE-1 (induced by source paper "View and style-independent action manifolds for human activity recognition"):
  with members:
    - "Transfer discriminant-analysis of canonical correlations for view-transfer action recognition"

Connected through hyperedge HE-2 (induced by source paper "HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion"):
  with members:
    - "Markov Random Field modeling, inference & learning in computer vision & image understanding: A survey"
    - "Discriminative learning of visual words for 3D human pose estimation"
    - "Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Mathematics