CLEAR Algorithm for Multi View Data Association
Channel: Kaveh Fathian
Date: 2022-12-10

This work presents the CLEAR (Consistent Lifting, Embedding, and Alignment Rectification) algorithm for multi-way data association. By leveraging insights from the multi-way matching and spectral graph clustering literature, CLEAR finds and rectifies erroneous data associations and returns consistent associations in a computationally efficient manner. Numerical experiments on both synthetic and real datasets demonstrate the scalability and superior performance of CLEAR in real-world problems. This algorithmic framework can provide significant improvement in the accuracy and efficiency of existing discrete assignment problems, which traditionally use pairwise (but potentially inconsistent) correspondences. An implementation of CLEAR is made publicly available online.

Paper: 
https://arxiv.org/abs/1902.02256

Code: 
https://github.com/mit-acl/clear