{
  "id": "1606.08315",
  "version": "v1",
  "published": "2016-06-27T15:23:04.000Z",
  "updated": "2016-06-27T15:23:04.000Z",
  "title": "Depth Estimation from Single Image using Sparse Representations",
  "authors": [
    "Yigit Oktar"
  ],
  "doi": "10.13140/RG.2.1.5059.0323",
  "categories": [
    "cs.CV"
  ],
  "abstract": "Monocular depth estimation is an interesting and challenging problem as there is no analytic mapping known between an intensity image and its depth map. Recently there has been a lot of data accumulated through depth-sensing cameras, in parallel to that researchers started to tackle this task using various learning algorithms. In this paper, a deep sparse coding method is proposed for monocular depth estimation along with an approach for deterministic dictionary initialization.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2016-06-27T15:23:04.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "single image",
      "sparse representations",
      "monocular depth estimation",
      "deep sparse coding method",
      "deterministic dictionary initialization"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}