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: "Clustering Local Motion Estimates for Robust and Efficient Object Tracking"
  Abstract: We present a new short-term tracking algorithm called Best Displacement Flow (BDF). This approach is based on the idea of ‘Flock of Trackers’ with two main contributions. The first contribution is the adoption of an efficient clustering approach to identify what we term the ‘Best Displacement’ vector, used to update the object’s bounding box. This clustering procedure is more robust than the median filter to high percentage of outliers. The second contribution is a procedure that we term ‘Consensus-Based Reinitialization’ used to reinitialize trackers that have previously been classified as outliers. For this reason we define a new tracker state called ‘transition’ used to sample new trackers in according to the current inlier trackers.

Connected through hyperedge HE-1 (induced by source paper "Online Object Tracking: A Benchmark"):
  with members:
    - "Robust object tracking via sparsity-based collaborative model"
    - "A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration"
    - "Object Tracking Benchmark"
    - "Multi attention module for visual tracking"

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