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Department of Information and Learning Technology National University of Tainan, Taiwan

Crowdsourcing Game Development for Collecting Benchmark Data of Facial Expression Recognition Systems. Department of Information and Learning Technology National University of Tainan, Taiwan. Hsin-Chih Lin, Zi-Jie Li and Wan-Ling Chu . Outline. Introduction. 01.

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Department of Information and Learning Technology National University of Tainan, Taiwan

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  1. Crowdsourcing Game Developmentfor Collecting Benchmark Data of Facial Expression Recognition Systems Department of Information and Learning Technology National University of Tainan, Taiwan Hsin-Chih Lin, Zi-Jie Li and Wan-Ling Chu

  2. Outline Introduction 01 Literature review 02 Crowdsourcing Game Development 03 Experimental Design and Results 04 Conclusions and Future Works 05 Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  3. Introduction • Developing an automatic expression recognition system • always use benchmarks • Most of facial pictures in benchmarks • not be accepted by the public or other teams • Manually classifying facial expression pictures • labor-expensive • time-consuming • difficult to standardize Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  4. Literature review • Crowdsourcing was first proposed by Howe (2006). • The concept of crowdsourcing • to rely on manpower to complete the work • difficult to be replaced by computer programs • Microtask & National Library of Finland • Mole Bridge • Mole Hunt Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  5. Literature review • Von Ahn (2006) proposed the concept of “Games with a Purpose” • attract online players through interactive games • “Gamification” can make boring becomes interesting (Krause & Smeddinck, 2011). • Listen Game(Turnbull et al., 2007) • improve the results of music search Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  6. Crowdsourcing Game Development Low Validity Database social ≠ automatic Feature Extraction Social classification system Face pictures Face Detection Classification expression pictures of low validity Crowdsourcing Game Automatic recognition system expression pictures of high validity High Validity Database Benchmark social = automatic Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  7. Crowdsourcing Game Development • 3 by 3 grid • seven pictures • expression hint • two options • Game-play rules • two minutes • randomly prompt an expression hint • none of the above • skip Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  8. Experimental Design and Results • This study enables crowds to classify facial expressions in the game during four-week experiments period • 100 participants • 1,416 times • Training and testing method of the automatic expression recognition system : • 80/20 • Incremental training Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  9. Experimental Design and Results Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  10. Experimental Design and Results Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  11. Experimental Design and Results Our study can effectively train automatic recognition system that allows the precision rate of system raised to extremely high in four-week testing. The dual system is able to develop an automatic recognition system in this study. Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  12. Experimental Design and Results • Our benchmark • 84 happiness • 51 sadness • 34 surprise • 30 anger Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  13. Conclusions and Future Works • An innovative dual systemmechanism • an organism • enhanced the extremely high precision rate of an automatic expression recognition system • efficiency and automation to classification that no matter how many facial expression data needs to be classified • resolve image classification or other issues must through human computation Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  14. Conclusions and Future Works • Crowdsourcing Game • boring become interesting • save more time and cost • get the classification results agree with crowds • Future Works • increase facial pictures • increase expressions categories(disgust, fear, nature) Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

  15. p6590043@hotmail.com Thank you for your attention. Pacific Neighborhood Consortium Annual Conference and Joint Meetings 2013

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