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: "Accelerometer-based gesture recognition using dynamic time warping and sparse representation"
  Abstract: In this paper, we propose a new accelerometer-based gesture recognition system. In this system, the start and end of the data collection process is automatically determined by acceleration waveform. In pretreatment phase, we propose a waveform compensation algorithm to solve the problems caused by the amplitude range of the accelerometer and use the coordinate transformation theory to alleviate the angle offset. In training phase, we use dynamic time warping (DTW) and affinity propagation (AP) to extract clusters and exemplars. We implement sparse representation for gesture recognition and propose a modified variable sparsity adaptive matching pursuit (MVSAMP) algorithm for signal reconstruction. This algorithm is more adapted to the characteristics of gesture recognition. In the classification stage, a method of weighted residuals is applied to improve the resolution of the best classification. To test the system's performance, a dictionary of 10 gestures is defined and a database consists of 3800 samples is created from 14 participants. Test results have shown that the proposed system achieves a good performance in a variety of experiments on Android platform.

Connected through hyperedge HE-1 (induced by source paper "Sparse Representation for Computer Vision and Pattern Recognition"):
  with members:
    - "Two-stage sparse representation for robust recognition on large-scale database"
    - "Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries"
    - "Robust object tracking via sparsity-based collaborative model"
    - "Multiple Kernel Learning for Hyperspectral Image Classification: A Review"
    - "Visual Object Tracking Using Structured Sparse PCA-Based Appearance Representation and Online Learning"
    - "A Probabilistic Framework for Discriminative Dictionary Learning"

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