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: "Multi-scale Deep Learning for Gesture Detection and Localization"
  Abstract: We present a method for gesture detection and localization based on multi-scale and multi-modal deep learning. Each visual modality captures spatial information at a particular spatial scale (such as motion of the upper body or a hand), and the whole system operates at two temporal scales. Key to our technique is a training strategy which exploits i) careful initialization of individual modalities; and ii) gradual fusion of modalities from strongest to weakest cross-modality structure. We present experiments on the ChaLearn 2014 Looking at People Challenge gesture recognition track, in which we placed first out of 17 teams.

Connected through hyperedge HE-1 (induced by source paper "Efficient Model-based 3D Tracking of Hand Articulations using Kinect"):
  with members:
    - "Real-time human pose recognition in parts from single depth images"
    - "3D Tracking of Multiple Objects with Identical Appearance Using RGB-D Input"
    - "Depth-Based Real-Time Hand Tracking with Occlusion Handling Using Kalman Filter and DAM-Shift"
    - "Characterizing Predicate Arity and Spatial Structure for Inductive Learning of Game Rules"

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: Computer science