research-article

Crowdsourced object segmentation with a game

Authors:

Vincent CharvillatAuthors Info & Claims

CrowdMM '13: Proceedings of the 2nd ACM international workshop on Crowdsourcing for multimedia

Pages 15 - 20

https://doi.org/10.1145/2506364.2506367

Published: 22 October 2013 Publication History

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Abstract

We introduce a new algorithm for image segmentation based on crowdsourcing through a game : Ask'nSeek. The game provides information on the objects of an image, under the form of clicks that are either on the object, or on the back-ground. These logs are then used in order to determine the best segmentation for an object among a set of candidates generated by the state-of-the-art CPMC algorithm. We also introduce a simulator that allows the generation of game logs and therefore gives insight about the number of games needed on an image to perform acceptable segmentation.

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Cited By

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Matin AMaduro Mde Leon Pereira RTremblay-Savard O(2020)Effect of Timer, Top Score and Leaderboard on Performance and Motivation in a Human Computing GameProceedings of the 15th International Conference on the Foundations of Digital Games10.1145/3402942.3403000(1-10)Online publication date: 15-Sep-2020
https://dl.acm.org/doi/10.1145/3402942.3403000
Newman AMcNamara BFosco CZhang YSukhum PTancik MKim NBylinskii ZBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention DataProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376799(1-13)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376799
Moradi MBayat FCharmi M(2019)Concept-Aware Web Image Compression Based on Crowdsourced Salient Object Detection2019 5th International Conference on Web Research (ICWR)10.1109/ICWR.2019.8765247(221-227)Online publication date: Apr-2019
https://doi.org/10.1109/ICWR.2019.8765247
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Index Terms

Crowdsourced object segmentation with a game
1. Human-centered computing
  1. Human computer interaction (HCI)

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Information

Published In

CrowdMM '13: Proceedings of the 2nd ACM international workshop on Crowdsourcing for multimedia

October 2013

44 pages

ISBN:9781450323963

DOI:10.1145/2506364

General Chairs:
Kuan-Ta Chen
Academia Sinica, Taiwan
,
Wei-Ta Chu
National Chung Cheng University, Taiwan
,
Martha Larson
Delft University of Technology, The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2013

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MM '13

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SIGMM

MM '13: ACM Multimedia Conference

October 22, 2013

Barcelona, Spain

Acceptance Rates

CrowdMM '13 Paper Acceptance Rate 8 of 16 submissions, 50%;

Overall Acceptance Rate 16 of 42 submissions, 38%

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Matin AMaduro Mde Leon Pereira RTremblay-Savard O(2020)Effect of Timer, Top Score and Leaderboard on Performance and Motivation in a Human Computing GameProceedings of the 15th International Conference on the Foundations of Digital Games10.1145/3402942.3403000(1-10)Online publication date: 15-Sep-2020
https://dl.acm.org/doi/10.1145/3402942.3403000
Newman AMcNamara BFosco CZhang YSukhum PTancik MKim NBylinskii ZBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention DataProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376799(1-13)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376799
Moradi MBayat FCharmi M(2019)Concept-Aware Web Image Compression Based on Crowdsourced Salient Object Detection2019 5th International Conference on Web Research (ICWR)10.1109/ICWR.2019.8765247(221-227)Online publication date: Apr-2019
https://doi.org/10.1109/ICWR.2019.8765247
Kerbiche AJabra SZagrouba ECharvillat V(2018)A robust video watermarking based on feature regions and crowdsourcingMultimedia Tools and Applications10.1007/s11042-018-5888-677:20(26769-26791)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1007/s11042-018-5888-6
Servadei LSchmidt REidelloth CMaier A(2018)Medical Monkeys: A Crowdsourcing Approach to Medical Big DataOn the Move to Meaningful Internet Systems. OTM 2017 Workshops10.1007/978-3-319-73805-5_9(87-97)Online publication date: 28-Jan-2018
https://doi.org/10.1007/978-3-319-73805-5_9
Kerbiche ABen Jabra SZagrouba ECharvillat V(2017)Robust Video Watermarking Approach Based on Crowdsourcing and Hybrid Insertion2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2017.8227489(1-8)Online publication date: Nov-2017
https://doi.org/10.1109/DICTA.2017.8227489
Marques O(2017)Using Games to Solve Challenging Multimedia ProblemsProgress in Intelligent Computing Techniques: Theory, Practice, and Applications10.1007/978-981-10-3373-5_2(27-35)Online publication date: 13-Jul-2017
https://doi.org/10.1007/978-981-10-3373-5_2
Murabito FPalazzo SSpampinato CGiordano D(2017)Implicit Vs. Explicit Human Feedback for Interactive Video Object SegmentationNew Trends in Image Analysis and Processing – ICIAP 201710.1007/978-3-319-70742-6_12(131-142)Online publication date: 31-Dec-2017
https://doi.org/10.1007/978-3-319-70742-6_12
Smyth BRafter RBanks SVassileva JBlustein JAroyo LD'Mello S(2016)Harnessing Crowdsourced Recommendation Preference Data from Casual GameplayProceedings of the 2016 Conference on User Modeling Adaptation and Personalization10.1145/2930238.2930260(95-104)Online publication date: 13-Jul-2016
https://dl.acm.org/doi/10.1145/2930238.2930260
Carlier ASalvador ACabezas FGiro-I-Nieto XCharvillat VMarques O(2016)Assessment of crowdsourcing and gamification loss in user-assisted object segmentationMultimedia Tools and Applications10.1007/s11042-015-2897-675:23(15901-15928)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1007/s11042-015-2897-6
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ImageNet Auto-Annotation with Segmentation Propagation

Collaborative Solving in a Human Computing Game Using a Market, Skills and Challenges

Likelihood-based feature relevance for figure-ground segmentation in images and videos

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