Robust and practical depth map fusion for time-of-flight cameras

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • University of Oulu

Kuvaus

Fusion of overlapping depth maps is an important part in many 3D reconstruction pipelines. Ideally fusion produces an accurate and nonredundant point cloud robustly even from noisy and partially poorly registered depth maps. In this paper, we improve an existing fusion algorithm towards a more ideal solution. Our method builds a nonredundant point cloud from a sequence of depth maps so that the new measurements are either added to the existing point cloud if they are in an area which is not yet covered or used to refine the existing points. The method is robust to outliers and erroneous depth measurements as well as small depth map registration errors due to inaccurate camera poses. The results show that the method overcomes its predecessor both in accuracy and robustness.

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoImage Analysis - 20th Scandinavian Conference, SCIA 2017, Proceedings
TilaJulkaistu - 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaScandinavian Conference on Image Analysis - Tromso, Norja
Kesto: 12 kesäkuuta 201714 kesäkuuta 2017
Konferenssinumero: 20

Julkaisusarja

NimiLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vuosikerta10269 LNCS
ISSN (painettu)03029743
ISSN (elektroninen)16113349

Conference

ConferenceScandinavian Conference on Image Analysis
LyhennettäSCIA
MaaNorja
KaupunkiTromso
Ajanjakso12/06/201714/06/2017

ID: 14244328