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: "SKEPRID: Pose and Illumination Change-Resistant Skeleton-Based Person Re-Identification"
  Abstract: Currently, the surveillance camera-based person re-identification is still challenging because of diverse factors such as people’s changing poses and various illumination. The various poses make it hard to conduct feature matching across images, and the illumination changes make color-based features unreliable. In this article, we present SKEPRID,1 a skeleton-based person re-identification method that handles strong pose and illumination changes jointly. To reduce the impacts of pose changes on re-identification, we estimate the joints’ positions of a person based on the deep learning technique and thus make it possible to extract features on specific body parts with high accuracy. Based on the skeleton information, we design a set of local color comparison-based cloth-type features, which are resistant to various lighting conditions. Moreover, to better evaluate SKEPRID, we build the PO8LI2 dataset, which has large pose and illumination diversity. Our experimental results show that SKEPRID outperforms state-of-the-art approaches in the case of strong pose and illumination variation.

Connected through hyperedge HE-1 (induced by source paper "Scalable Person Re-identification: A Benchmark"):
  with members:
    - "Query-driven iterated neighborhood graph search for large scale indexing"
    - "Online Inter-Camera Trajectory Association Exploiting Person Re-Identification and Camera Topology"

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