• Click'n'Cut: crowdsour...

*Result*: Click'n'Cut: crowdsourced interactive segmentation with object candidates ; Click'n'Cut

Title:
Click'n'Cut: crowdsourced interactive segmentation with object candidates ; Click'n'Cut
Authors:
Carlier, Axel, Charvillat, Vincent, Salvador, Amaia, Giro-I-Nieto, Xavier, Marques, Oge
Contributors:
Real Expression Artificial Life (IRIT-REVA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Institut National Polytechnique (Toulouse) (Toulouse INP), Universitat Politècnica de Catalunya Barcelona (UPC), Florida Atlantic University Boca Raton, ACM
Source:
CrowdMM '14: Proceedings of the 2014 International ACM Workshop on Crowdsourcing for Multimedia ; International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM 2014) @ MM 2014 ; https://hal.science/hal-04080198 ; International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM 2014) @ MM 2014, ACM, Nov 2014, Orlando, United States. pp.53-56, ⟨10.1145/2660114.2660125⟩ ; https://dl.acm.org/doi/10.1145/2660114.2660125
Publisher Information:
HAL CCSD
ACM
Publication Year:
2014
Collection:
Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
Subject Terms:
Crowdsourcing, Object segmentation, Object candidates, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Subject Geographic:
Orlando, United States
Document Type:
*Conference* conference object
Language:
English
ISBN:
978-1-4503-3128-9
1-4503-3128-9
Relation:
hal-04080198; https://hal.science/hal-04080198; https://hal.science/hal-04080198/document; https://hal.science/hal-04080198/file/carlier_13294.pdf; OATAO: 13294
DOI:
10.1145/2660114.2660125
Availability:
https://hal.science/hal-04080198
https://hal.science/hal-04080198/document
https://hal.science/hal-04080198/file/carlier_13294.pdf
https://doi.org/10.1145/2660114.2660125
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edsbas.D542B38
Database:
BASE

*Further Information*

*National audience ; This paper introduces Click'n'Cut, a novel web tool for interactive object segmentation addressed to crowdsourcing tasks. Click'n'Cut combines bounding boxes and clicks generated by workers to obtain accurate object segmentations. These segmentations are created by combining precomputed object candidates in a light computational fashion that allows an immediate response from the interface. Click'n'Cut has been tested with a crowdsourcing campaign to annotate a subset of the Berkeley Segmentation Dataset (BSDS). Results show competitive results with state of the art, especially in time to converge to a high quality segmentation. The data collection campaign included golden standard tests to detect cheaters.*