Effect of keyframes extraction from thermal infrared video stream to generate dense point cloud of the building's facade

S. Motayyeb, F. Samadzadegan, F. Dadrass javan, H. r. Hosseinpour

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

1 Citation (Scopus)

Abstract

Keyframes extraction is required and effective for the 3D reconstruction of objects from a thermal video sequence to increase geometric accuracy, reduce the volume of aerial triangulation calculations, and generate the dense point cloud. The primary goal and focus of this paper are to assess the effect of keyframes extraction from the thermal infrared video sequence on the geometric accuracy of the dense point cloud generated. The method of keyframes extraction of thermal infrared video presented in this paper consists of three basic steps. (A) The ability to identify and remove blur frames from non-blur frames in a sequence of recorded frames. (B) The ability to apply the standard baseline condition between sequence frames to establish the overlap condition and prevent the creation of degeneracy conditions. (C) Evaluating degeneracy conditions and keyframes extraction using Geometric Robust Information Criteria (GRIC). The performance evaluation criteria for keyframes extraction in the generation of the thermal infrared dense point cloud in this paper are to assess the increase in density of the generated three-dimensional point cloud and reduce reprojection error. Based on the results and assessments presented in this paper, using keyframes increases the density of the thermal infrared dense point cloud by about 0.03% to 0.10% of points per square meter. It reduces the reprojection error by about 0.005% of pixels (2 times).
Original languageEnglish
Title of host publicationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
EditorsM.R. Delavar, R. Ali Abbaspour, S. Farzaneh
Place of PublicationTehran
PublisherCopernicus
Pages551-561
VolumeX-4/W1-2022
DOIs
Publication statusPublished - 14 Jan 2023
EventGeoSpatial Conference 2022 - virtual, Tehran, Iran, Islamic Republic of
Duration: 19 Feb 202322 Feb 2023
https://www.sru.ac.ir/en/4860-2/

Publication series

NameISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
PublisherCopernicus
ISSN (Print)2194-9042

Conference

ConferenceGeoSpatial Conference 2022
Country/TerritoryIran, Islamic Republic of
CityTehran
Period19/02/2322/02/23
OtherJoint 6th SMPR and 4th GIResearch Conferences
Internet address

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