loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Affiliation

Select a Subject

Univ Lyon, Lyon 2, LIRIS, F-69676 Lyon, France, Unité Cancer et Environnement, Centre Léon Bérard, Lyon, France, Agence de l’Environnement et de la Maítrise de l’Energie, Angers and France
Context (please use complete words only)
Field
Sort by

1 Papers

Efficient Bark Recognition in the Wild

Topics: Color and Texture Analyses; Features Extraction

Authors: Rémi Ratajczak 1 , Sarah Bertrand 2 , Carlos Crispim-Junior 2 and Laure Tougne 2

Affiliations: 1 Univ Lyon, Lyon 2, LIRIS, F-69676 Lyon, France, Unité Cancer et Environnement, Centre Léon Bérard, Lyon, France, Agence de l’Environnement et de la Maítrise de l’Energie, Angers and France , 2 Univ Lyon, Lyon 2, LIRIS, F-69676 Lyon and France

Digital Object Identifier: 10.5220/0007361902400248

Proceedings of VISAPP 2019/VISIGRAPP, ISBN: 978-989-758-354-4

Collapse Button Quick Abstract
In this study, we propose to address the difficult task of bark recognition in the wild using computationally efficient and compact feature vectors. We introduce two novel generic methods to significantly reduce the dimensions of existing texture and color histograms with few losses in accuracy. Specifically, we propose a straightforward yet efficient way to compute Late Statistics from texture histograms and an approach to iteratively quantify the color space based on domain priors. We further combine the reduced histograms in a late fusion manner to benefit from both texture and color cues. Results outperform state-of-the-art methods by a large margin on four public datasets respectively composed of 6 bark classes (BarkTex, NewBarkTex), 11 bark classes (AFF) and 12 bark classes (Trunk12). In addition to these experiments, we propose a baseline study on Bark-101, a new challenging dataset including manually segmented images of 101 bark classes that we release publicly.
Collapse Button Related Ontology Subjects/Areas/Topics (4)
Color and Texture Analyses

Features Extraction

Image and Video Analysis
Computer Vision, Visualization and Computer Graphics

Topic(s):

Filter listed results, by

Author
Locate Author in list below
Add Author(s) to filter:

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic