Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0

Marine imaging has evolved from small, narrowly focussed applications to large-scale applications covering areas of several hundred square kilometers or time series covering observation periods of several months. The analysis and interpretation of the accumulating large volume of digital images or v...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Martin Zurowietz, Tim W. Nattkemper
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	marine imaging image annotation video annotation environmental monitoring machine learning Science Q General. Including nature conservation, geographical distribution QH1-199.5
Acceso en línea:	https://doaj.org/article/ae2ccb1590f04bffb1d473e9ab4f06f8
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ae2ccb1590f04bffb1d473e9ab4f06f8
record_format	dspace
spelling	oai:doaj.org-article:ae2ccb1590f04bffb1d473e9ab4f06f82021-12-01T18:25:59ZCurrent Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.02296-774510.3389/fmars.2021.760036https://doaj.org/article/ae2ccb1590f04bffb1d473e9ab4f06f82021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmars.2021.760036/fullhttps://doaj.org/toc/2296-7745Marine imaging has evolved from small, narrowly focussed applications to large-scale applications covering areas of several hundred square kilometers or time series covering observation periods of several months. The analysis and interpretation of the accumulating large volume of digital images or videos will continue to challenge the marine science community to keep this process efficient and effective. It is safe to say that any strategy will rely on some software platform supporting manual image and video annotation, either for a direct manual annotation-based analysis or for collecting training data to deploy a machine learning–based approach for (semi-)automatic annotation. This paper describes how computer-assisted manual full-frame image and video annotation is currently performed in marine science and how it can evolve to keep up with the increasing demand for image and video annotation and the growing volume of imaging data. As an example, observations are presented how the image and video annotation tool BIIGLE 2.0 has been used by an international community of more than one thousand users in the last 4 years. In addition, new features and tools are presented to show how BIIGLE 2.0 has evolved over the same time period: video annotation, support for large images in the gigapixel range, machine learning assisted image annotation, improved mobility and affordability, application instance federation and enhanced label tree collaboration. The observations indicate that, despite novel concepts and tools introduced by BIIGLE 2.0, full-frame image and video annotation is still mostly done in the same way as two decades ago, where single users annotated subsets of image collections or single video frames with limited computational support. We encourage researchers to review their protocols for education and annotation, making use of newer technologies and tools to improve the efficiency and effectivity of image and video annotation in marine science.Martin ZurowietzTim W. NattkemperFrontiers Media S.A.articlemarine imagingimage annotationvideo annotationenvironmental monitoringmachine learningScienceQGeneral. Including nature conservation, geographical distributionQH1-199.5ENFrontiers in Marine Science, Vol 8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	marine imaging image annotation video annotation environmental monitoring machine learning Science Q General. Including nature conservation, geographical distribution QH1-199.5
spellingShingle	marine imaging image annotation video annotation environmental monitoring machine learning Science Q General. Including nature conservation, geographical distribution QH1-199.5 Martin Zurowietz Tim W. Nattkemper Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0
description	Marine imaging has evolved from small, narrowly focussed applications to large-scale applications covering areas of several hundred square kilometers or time series covering observation periods of several months. The analysis and interpretation of the accumulating large volume of digital images or videos will continue to challenge the marine science community to keep this process efficient and effective. It is safe to say that any strategy will rely on some software platform supporting manual image and video annotation, either for a direct manual annotation-based analysis or for collecting training data to deploy a machine learning–based approach for (semi-)automatic annotation. This paper describes how computer-assisted manual full-frame image and video annotation is currently performed in marine science and how it can evolve to keep up with the increasing demand for image and video annotation and the growing volume of imaging data. As an example, observations are presented how the image and video annotation tool BIIGLE 2.0 has been used by an international community of more than one thousand users in the last 4 years. In addition, new features and tools are presented to show how BIIGLE 2.0 has evolved over the same time period: video annotation, support for large images in the gigapixel range, machine learning assisted image annotation, improved mobility and affordability, application instance federation and enhanced label tree collaboration. The observations indicate that, despite novel concepts and tools introduced by BIIGLE 2.0, full-frame image and video annotation is still mostly done in the same way as two decades ago, where single users annotated subsets of image collections or single video frames with limited computational support. We encourage researchers to review their protocols for education and annotation, making use of newer technologies and tools to improve the efficiency and effectivity of image and video annotation in marine science.
format	article
author	Martin Zurowietz Tim W. Nattkemper
author_facet	Martin Zurowietz Tim W. Nattkemper
author_sort	Martin Zurowietz
title	Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0
title_short	Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0
title_full	Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0
title_fullStr	Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0
title_full_unstemmed	Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0
title_sort	current trends and future directions of large scale image and video annotation: observations from four years of biigle 2.0
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/ae2ccb1590f04bffb1d473e9ab4f06f8
work_keys_str_mv	AT martinzurowietz currenttrendsandfuturedirectionsoflargescaleimageandvideoannotationobservationsfromfouryearsofbiigle20 AT timwnattkemper currenttrendsandfuturedirectionsoflargescaleimageandvideoannotationobservationsfromfouryearsofbiigle20
_version_	1718404713816260608

Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0

Ejemplares similares