A dense depth estimation method using superpixels

Feng Jin, Xuefeng Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Conventional stereo matching or depth estimation algorithms always provide incomplete disparity map. These pixels without depth estimation in the map are named depth gaps. Weak texture and occluded areas are main source of depth gaps. We propose a novel method to assign good depth estimation on the areas above. Our algorithm combines state-of-art superpixel segmentation approach and linear filter. First we do superpixel segmentation on reference image, after this every pixel has a label determines which superpixel it belongs to. Then merging distance between superpixels in spatial space and color space, we apply linear filter on every superpixel. We evaluate the performance of our algorithm with some classic stereo datasets to show the promotion we obtained.

Original languageEnglish
Title of host publication2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages290-294
Number of pages5
ISBN (Electronic)9781467382663
DOIs
Publication statusPublished - 16 Jun 2016
Event12th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2015 - Chengdu, China
Duration: 18 Dec 201520 Dec 2015

Publication series

Name2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2015

Conference

Conference12th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2015
Country/TerritoryChina
CityChengdu
Period18/12/1520/12/15

Keywords

  • Depth estimation
  • Stereo matching
  • linear filter
  • superpixel segmentation

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