Stereo and Active-Sensor Data Fusion for Improved Stereo Block Matching

Stefan-Daniel Suvei, Leon Bodenhagen, Lilita Kiforenko, Peter Christiansen, Rasmus Nyholm Jørgensen, Anders Glent Buch, Norbert Krüger

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


This paper proposes an algorithm which uses the depth information acquired from an active sensor as guidance for a block matching stereo algorithm. In the proposed implementation, the disparity search interval used for the block matching is reduced around the depth values obtained from the active sensor, which leads to an improved matching quality and denser disparity maps and point clouds. The performance of the proposed method is evaluated by carrying out a series of experiments on 3 different data sets obtained from different robotic systems. We demonstrate with experimental results that the disparity estimation is improved and denser disparity maps are generated.

Original languageEnglish
Title of host publicationImage Analysis and Recognition : 13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel, Póvoa de Varzim, Portugal, July 13-15, 2016, Proceedings
EditorsAurélio Campilho, Fakhri Karray
Publication dateJul 2016
ISBN (Print)978-3-319-41500-0
ISBN (Electronic)978-3-319-41501-7
Publication statusPublished - Jul 2016
Event13th International Conference on Image Analysis and Recognition - Póvoa de Varzim, Portugal
Duration: 13. Jul 201615. Jul 2016


Conference13th International Conference on Image Analysis and Recognition
CityPóvoa de Varzim
Internet address
SeriesLecture Notes in Computer Science


Dive into the research topics of 'Stereo and Active-Sensor Data Fusion for Improved Stereo Block Matching'. Together they form a unique fingerprint.

Cite this