DASC (Dense Adaptive Self-Correlation) Descriptor

Version 2.0 (14 Apr. 2016)

Contributed by Seungryong Kim (srkim89@yonsei.ac.kr).

This code is written in MATLAB, and implements the DASC descriptor [project website].

Usage

1. mex mexDASC.cpp
2. setup SIFTflow code [2]
3. start main.m

Parameters

• M_half: half size of large window M
• N_half: half size of large window N
• epsil: epsilon for FastGuidedFilter [3]
• downSize: downsize factor s for FastGuidedFilter [3]
• sigma_s: for recursive filter (RF) [4]
• sigma_r: for recursive filter (RF) [4]
• iter: for recursive filter (RF) [4]

Input and Output

• Input: input image 1 (e.g., img1.png), input image 2 (e.g., img2.png)
• Output: warped image from image 2 (e.g., warp2.png), flow result (e.g., flow.png)

Notes

• The code is provided for academic use only. Use of the code in any commercial or industrial related activities is prohibited.
• If you use our code, please cite the paper.

@InProceedings{Kim2015,
author = {Seungryong Kim and Dongbo Min and Bumsub Ham and Seungchul Ryu and Minh N. Do and Kwanghoon Sohn},
title = {DASC: Dense Adaptive Self-Correlation Descriptor for Multi-modal and Multi-spectral Correspondence},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE},
year = {2015}
}

References

[1] S. Kim, D. Min, B. Ham, S. Ryu, M. N. Do., and K. Sohn, DASC: Dense Adaptive Self-Correlation Descriptor for Multi-modal and Multi-spectral Correspondence, In Proc. of CVPR, 2015.

[2] C. Liu, J. Yuen, and A. Torralba. Sift flow: Dense correspondenceacross scenes and its applications. IEEE TPAMI, 33(5), pp. 815-830, 2011.

[3] K. He and J. Sun, Fast Guided Filter, arXiv, 2015.

[4] S. L. Eduardo and M. M. Oliveira, Domain transform for edge-aware image and video processing, ACM ToG, 30(4), 2011.