{
  "id": "1506.06274",
  "version": "v1",
  "published": "2015-06-20T17:55:49.000Z",
  "updated": "2015-06-20T17:55:49.000Z",
  "title": "Pose Estimation Based on 3D Models",
  "authors": [
    "Chuiwen Ma",
    "Hao Su",
    "Liang Shi"
  ],
  "categories": [
    "cs.CV",
    "cs.LG",
    "cs.RO"
  ],
  "abstract": "In this paper, we proposed a pose estimation system based on rendered image training set, which predicts the pose of objects in real image, with knowledge of object category and tight bounding box. We developed a patch-based multi-class classification algorithm, and an iterative approach to improve the accuracy. We achieved state-of-the-art performance on pose estimation task.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2015-06-20T17:55:49.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "3d models",
      "pose estimation system",
      "patch-based multi-class classification algorithm",
      "pose estimation task",
      "real image"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}