Joint Geodesic Upsampling of Depth Images

    •  Liu, M.-Y., Tuzel, O., Taguchi, Y., "Joint Geodesic Upsampling of Depth Images", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), DOI: 10.1109/​CVPR.2013.29, June 2013, pp. 169-176.
      BibTeX TR2013-042 PDF Software
      • @inproceedings{Liu2013jun,
      • author = {Liu, M.-Y. and Tuzel, O. and Taguchi, Y.},
      • title = {Joint Geodesic Upsampling of Depth Images},
      • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2013,
      • pages = {169--176},
      • month = jun,
      • doi = {10.1109/CVPR.2013.29},
      • issn = {1063-6919},
      • url = {}
      • }
  • Research Area:

    Computer Vision

TR Image
Visual comparison. Visual comparison of the depth upsampling results at 8x upsampling rate. From left to right, the columns correspond to input color image, ground truth depth images, output of the QUAD algorithm, output of the JBU algorithm, and output of the proposed algorithm. The proposed algorithm produces the sharpest depth boundaries with the fewest artifacts.

We propose an algorithm utilizing geodesic distances to upsample a low resolution depth image using a registered high resolution color image. Specifically, it computes depth for each pixel in the high resolution image using geodesic paths to the pixels whose depths are known from the low resolution one. Though this is closely related to the all-pairshortest-path problem which has O(n2 log n) complexity, we develop a novel approximation algorithm whose complexity grows linearly with the image size and achieve realtime performance. We compare our algorithm with the state of the art on the benchmark dataset and show that our approach provides more accurate depth upsampling with fewer artifacts. In addition, we show that the proposed algorithm is well suited for upsampling depth images using binary edge maps, an important sensor fusion application.


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