Depth estimation from the color drift of a route panorama

Hajime Nagahara, Atsushi Ichikawa, Masahiko Yachida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Image based modeling methods has been well studied for generating a 3D model from an image sequence. Most of them require redundant and huge spatio-temporal images for estimating a scene depth. It is not good characteristic for taking a higher resolution of texture. A route panorama is a continuous panoramic image along a path. It is suitable for modeling large environments such as a city or town. The panorama captured by a line scan sensor also has advantage for capturing higher resolution easily. In this paper, we propose a method for depth estimation from the panorama. The route panorama has color drifts that correspond to the distances of captured objects. We use these color drifts to estimate the depth of an image. The proposed method detects the color drift by window matching using Belief Propagation. It also uses a Gaussian Pyramid to stabilize the estimation and decrease its computation cost. We confirmed that the proposed method estimated depth maps from a single high-resolution panorama in experiments.

Original languageEnglish
Title of host publication2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Pages4066-4071
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS - Nice, France
Duration: Sep 22 2008Sep 26 2008

Other

Other2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
CountryFrance
CityNice
Period9/22/089/26/08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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