{
  "id": "1505.06079",
  "version": "v1",
  "published": "2015-05-22T13:48:10.000Z",
  "updated": "2015-05-22T13:48:10.000Z",
  "title": "Robust Rotation Synchronization via Low-rank and Sparse Matrix Decomposition",
  "authors": [
    "Federica Arrigoni",
    "Andrea Fusiello",
    "Beatrice Rossi",
    "Pasqualina Fragneto"
  ],
  "comment": "Submitted to IJCV",
  "categories": [
    "cs.CV"
  ],
  "abstract": "This paper deals with the rotation synchronization problem, which arises in global registration of 3D point-sets and in structure from motion. The problem is formulated in an unprecedented way as a \"low-rank and sparse\" matrix decomposition that handles both outliers and missing data. A minimization strategy, dubbed R-GoDec, is also proposed and evaluated experimentally against state-of-the-art algorithms on simulated and real data. The results show that R-GoDec is the fastest among the robust algorithms.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2015-05-22T13:48:10.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "sparse matrix decomposition",
      "robust rotation synchronization",
      "rotation synchronization problem",
      "paper deals",
      "robust algorithms"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}