by Liu, D and Klette, R
Abstract:
We present a method for refining depth information generated by a stereo-matching algorithm with the goal to provide depthaware photo-effect applications. Our key idea is to use structural features of the base image to enhance the depth information. Our method preprocesses the original disparity map by revising the sky region and removing incorrect data (on the left-side of the disparity map) caused by occlusion. The base image is mean-shift segmented. A median filter is applied on the disparity map within each segment. Invalid step-edges in the disparity map are removed by a joint bilateral filter. Experiments show that our method can revise holes, inaccurate object edges, speckle noises, and invalid step-edges from the given depth information. Results illustrate the applicability for photo editing.
Reference:
Stereo refinement for photo editing (Liu, D and Klette, R), In Computer Vision and Graphics, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, volume 8671, 2014.
Bibtex Entry:
@inproceedings{liu2014stereoediting,
author = "Liu, D and Klette, R",
booktitle = "Computer Vision and Graphics, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
organization = "Warsaw",
pages = "391--399",
publisher = "Springer Verlag",
title = "Stereo refinement for photo editing",
volume = "8671",
year = "2014",
abstract = "We present a method for refining depth information generated by a stereo-matching algorithm with the goal to provide depthaware photo-effect applications. Our key idea is to use structural features of the base image to enhance the depth information. Our method preprocesses the original disparity map by revising the sky region and removing incorrect data (on the left-side of the disparity map) caused by occlusion. The base image is mean-shift segmented. A median filter is applied on the disparity map within each segment. Invalid step-edges in the disparity map are removed by a joint bilateral filter. Experiments show that our method can revise holes, inaccurate object edges, speckle noises, and invalid step-edges from the given depth information. Results illustrate the applicability for photo editing.",
startyear = "2014",
startmonth = "Sep",
startday = "17",
finishyear = "2014",
finishmonth = "Sep",
finishday = "19",
issn = "0302-9743",
eissn = "1611-3349",
keyword = "Photo editing",
keyword = "Stereo refinement",
keyword = "Stereo vision",
language = "eng",
conference = "International Conference in Computer Vision and Graphics",
}