adfsm's Introduction

ADfSM

(ADfSM: All-around Depth from Small Motion)

Source code and datasets for the paper:

S. Im, H. Ha, F. Rameau, H.-G. Jeon, G. Choe and I.S. Kweon, All-around Depth from Small Motion with A Spherical Panoramic Camera - ECCV 2016

Project page

Dependency

How to run

run main.m

Important Information

Frame selection

The current implementation uses only the first 30 frames of your video clip. If you want to try with a different number of images or different sampling rate, please change 'setting.sam_rate'.

Dense matching step

We implemented the function "DenseMatching" to receive a scale for image downsampling and the number of labels for your convenience in testing. (Default: 0.5 scale and 64 labels for quick tests, you can change them ('setting.scaling, 'setting.num_label')

For the depth refinement, we utilized a tree-based depth upsampling approach [1,2].

Authors

IMPORTANT: If you use this software please cite the following in any resulting publication:

@inproceedings{im2016all,
  title={All-Around Depth from Small Motion with a Spherical Panoramic Camera},
  author={Im, Sunghoon and Ha, Hyowon and Rameau, Fran{\c{c}}ois and Jeon, Hae-Gon and Choe, Gyeongmin and Kweon, In So},
  booktitle={European Conference on Computer Vision},
  pages={156--172},
  year={2016},
  organization={Springer}
}

References

Yang, Qingxiong. "Stereo matching using tree filtering." IEEE transactions on pattern analysis and machine intelligence 37.4 (2015): 834-846.
Yang, Qingxiong. "A non-local cost aggregation method for stereo matching." Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2012.

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