2-point RANSAC for scene image matching under large viewpoint changes

Chih Chung Chou, Chieh-Chih Wang

Research output: Contribution to journalConference articlepeer-review

8 Scopus citations

Abstract

This work aims to accurately match two scene images under large viewpoint changes, which is the key issue in appearance-based localization tasks. In this paper, two key ideas are proposed to solve the challenging problem. First, to detect extreme small overlapping regions between two images, a new approach is developed to estimate the camera motion using only two pairs of matched features, while the state-of-art needs at least five. Second, proper prior knowledge to the environmental structures is utilized to strengthen the outlier rejection. The proposed 2-point approach is tested on challenging scenes and shows good robustness to the drastic occlusion and scaling caused by viewpoint changes.

Original languageEnglish
Article number7139705
Pages (from-to)3646-3651
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Volume2015-June
Issue numberJune
DOIs
StatePublished - 29 Jun 2015
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: 26 May 201530 May 2015

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