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題名 以情境與行為意向分析為基礎之持續性概念重構個人化影像標籤系統
Continuous Reconceptualization of Personalized Photograph Tagging System Based on Contextuality and Intention作者 李俊輝 貢獻者 郭正佩<br>楊立行
Kuo, Pei Jeng<br>Yang, Lee Xieng
李俊輝關鍵詞 個人生命記憶典藏
影像標籤自動化
階層式貝氏網路
認知模擬
personal archiving
automatic image-tagging
hierarchical bayesian network
cognitive modeling日期 2014 上傳時間 2-三月-2015 10:13:38 (UTC+8) 摘要 生活於數位時代，巨量的個人生命記憶使得人們難以輕易解讀，必須經過檢索或標籤化才可以進一步瞭解背後的意涵。本研究著力個人記憶裡繁瑣及週期性的廣泛事件，進行於「情節記憶語意化」以及「何以權衡大眾與個人資訊」兩議題之探討。透過生命記憶平台裡影像標籤自動化功能，我們以時空資訊為索引提出持續性概念重構模型，整合共同知識、個人近況以及個人偏好三項因素，模擬人們對每張照片下標籤時的認知歷程，改善其廣泛事件上註釋困難。在實驗設計上，實作大眾資訊模型、個人資訊模型以及本研究持續性概念重構模型，並招收九位受試者來剖析其認知歷程以及註釋效率。實驗結果顯示持續性概念重構模型解決了上述大眾與個人兩模型上的極限，即舊地重遊、季節性活動、非延續性活動性質以及資訊邊界註釋上的問題，因此本研究達成其個人生命記憶在廣泛事件之語意標籤自動化示範。
In the digital era, labeling and retrieving are ways to understand the meaning behind a huge amount of lifetime archive. Foucusing on tedious and periodic general events, this study will discuss two issues: (1) the semantics of episodic memory (2) the trade-off between common and personal knowledge. Using the automatic image-tagging technique of lifelong digital archiving system, we propose the Coutinuous Reconceptualization Model which models the cognitive processing of examplar categorization based on temporal-spatial information. Integrating the common knowlegde, current personal life and hobby, the Continuous Reconceptualization Model improves the tagging efficiency. In this experiment, we compare the accuracy of cognitive modeling and tagging efficiency of the three distinct models: the common knowledge model, personal knowledge model and Coutinuous Reconceptualization Model. Nine participants were recruited to label the photos. The results show that the Continous Reconceptualization Model overcomes the limitations inherent in other models, including the auto-tagging problems of modeling certain situations, such as re-visiting places, seasonal activities, noncontinuous activities and information boundary. Consequently, the Continuous Reconceptualization Model demonstrated the efficiency of the automatic image-tagging technique used in the semantic labeling of the general event of personal memory.參考文獻 [1] D. L. Schacter, The Seven Sins of Memory: How the Mind Forgets and Remembers. Houghton Mifflin Harcourt, 2002.[2] G. Bell, “A personal digital store,” Commun. ACM, vol. 44, pp. 86–91, 2001.[3] J. Gemmell, G. Bell, and R. Lueder, “MyLifeBits: a personal database for everything,” Commun. ACM, vol. 49, no. 1, pp. 88–95, 2006.[4] M. Conway and C. Pleydell-Pearce, “The construction of autobiographical memories in the self-memory system.,” Psychol. Rev., vol. 107, no. 2, pp. 261–288, 2000.[5] E. Berry, N. Kapur, L. Williams, S. Hodges, P. Watson, G. Smyth, J. Srinivasan, R. Smith, B. Wilson, and K. Wood, “The use of a wearable camera, SenseCam, as a pictorial diary to improve autobiographical memory in a patient with limbic encephalitis: a preliminary report.,” Neuropsychol. Rehabil., vol. 17, no. 4–5, pp. 582–601, 2007.[6] J. Liu and P. Dolan, “Personalized news recommendation based on click behavior,” in Proceedings of the 15th, 2010.[7] P. Maglio and R. Barrett, “Intermediaries personalize information streams,” Commun. ACM, vol. 43, no. 8, pp. 96–101, 2000.[8] L. Von Ahn, B. Maurer, C. Mcmillen, D. Abraham, and M. Blum, “reCAPTCHA: Human-Based Character Recognition via Web Security Measures,” Science (80-. )., vol. 321, no. 5895, pp. 1465–1468, 2008.[9] J. Lanier, You are Not a Gadget: A Manifesto. Alfred A. Knopf, 2010.[10] C. G. Bell and J. Gemmell, Total Recall: How the E-Memory Revolution Will Change Everything. Dutton, 2009.[11] L. R. Squire, “Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans.,” Psychol. Rev., vol. 99, no. 2, pp. 195–231, 1992.[12] E. Tulving, “Episodic and semantic memory 1,” Organ. Mem. London Acad., vol. 381, p. e402, 1972.[13] W. James, The Principles of Psychology, no. 第 1 卷. Cosimo, Incorporated, 2007.[14] J.-M. Guyau, “La gen{è}se de l’id{é}e de temps [The origin of the idea of time],” Guyau idea time, pp. 37–90, 1988.[15] T. Ribot, Diseases of memory. Appleton, 1887.[16] E. F. Loftus, Eyewitness testimony. Harvard University Press, 1996.[17] B. K. Jones and D. P. McAdams, “Becoming Generative: Socializing Influences Recalled in Life Stories in Late Midlife,” J. Adult Dev., vol. 20, no. 3, pp. 158–172, Jul. 2013.[18] D. McAdams, “The psychology of life stories.,” Rev. Gen. Psychol., 2001.[19] M. B. Brewer and W. Gardner, “Who is this ‘We’? Levels of collective identity and self representations.,” J. Pers. Soc. Psychol., vol. 71, no. 1, pp. 83–93, 1996.[20] C. C. Marshall, “Challenges and Opportunities for Personal Digital Archiving.”,” Digit. Pers. Collect. Digit. Era, pp. 90–114, 2011.[21] I. Cole, “Human aspects of office filing: Implications for the electronic office,” in Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 1982, vol. 26, no. 1, pp. 59–63.[22] D. Barreau and B. A. Nardi, “Finding and Reminding: File Organization from the Desktop,” SIGCHI Bull., vol. 27, no. 3, pp. 39–43, 1995.[23] D. Barreau, “The persistence of behavior and form in the organization of personal information,” J. Am. Soc. Inf. Sci. Technol., vol. 59, no. 2, pp. 307–317, 2008.[24] P. Galloway, “I, Digital: Personal Collections in the Digital Era. Edited by Christopher A. Lee,” J. Am. Soc. Inf. Sci. Technol., vol. 63, no. 6, pp. 1278–1279, 2012.[25] G. J. F. Jones, C. Gurrin, L. Kelly, D. Byrne, and Y. Chen, “Information access tasks and evaluation for personal lifelogs,” 2008.[26] D. Byrne, L. Kelly, and G. J. F. Jones, “Multiple multimodal mobile devices: Lessons learned from engineering lifelog solutions,” 2012.[27] C. Dobbins, M. Merabti, P. Fergus, and D. Llewellyn-Jones, “Creating human digital memories for a richer recall of life experiences,” Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on. pp. 246–251, 2013.[28] C. Dobbins, M. Merabti, P. Fergus, and D. Llewellyn-Jones, “Creating human digital memories with the aid of pervasive mobile devices,” Pervasive Mob. Comput., vol. 12, pp. 160–178, 2014.[29] C. Dobbins, M. Merabti, P. Fergus, and D. Llewellyn-Jones, “Capturing Human Digital Memories for Assisting Memory Recall,” in Advances in Physiological Computing, Springer London, 2014, pp. 211–234.[30] A. R. Doherty, K. Pauly-Takacs, N. Caprani, C. Gurrin, C. J. A. Moulin, N. E. O’Connor, and A. F. Smeaton, “Experiences of Aiding Autobiographical Memory Using the SenseCam,” Human–Computer Interact., vol. 27, no. 1–2, pp. 151–174, 2012.[31] E. Hoven and B. Eggen, “Informing Augmented Memory System Design Through Autobiographical Memory Theory,” Pers. Ubiquitous Comput., vol. 12, no. 6, pp. 433–443, 2008.[32] D. Byrne and G. J. F. Jones, “Towards computational autobiographical narratives through human digital memories,” in Proceedings of the 2nd ACM international Workshop on Story Representation, Mechanism and Context, 2008, pp. 9–12.[33] D. Pavel, V. Callaghan, and A. K. Dey, “Supporting Wellbeing Through Improving Interactions and Understanding in Self-Monitoring Systems.” 2012.[34] B. Kikhia, J. Hallberg, J. E. Bengtsson, S. Savenstedt, and K. Synnes, “Building Digital Life Stories for Memory Support,” Int. J. Comput. Heal., vol. 1, no. 2, pp. 161–176, 2010.[35] M. Crete-Nishihata, R. M. Baecker, M. Massimi, D. Ptak, R. Campigotto, L. D. Kaufman, A. M. Brickman, G. R. Turner, J. R. Steinerman, and S. E. Black, “Reconstructing the Past: Personal Memory Technologies Are Not Just Personal and Not Just for Memory,” Human–Computer Interact., vol. 27, no. 1–2, pp. 92–123, 2012.[36] E. van den Hoven, C. Sas, and S. Whittaker, “Introduction to this Special Issue on Designing for Personal Memories: Past, Present, and Future,” Human–Computer Interact., vol. 27, no. 1–2, pp. 1–12, 2012.[37] D. Draaisma, Vergeetboek. Historische Uitgeverij, 2010.[38] A. J. Sellen and S. Whittaker, “Beyond total capture: a constructive critique of lifelogging,” Commun. ACM, vol. 53, no. 5, pp. 70–77, 2010.[39] L. Wittgenstein, P. M. S. Hacker, and J. Schulte, Philosophical Investigations. Wiley, 2010.[40] E. E. Smith and D. L. Medin, Categories and concepts. Harvard University Press Cambridge, MA, 1981.[41] B. H. Ross, “This is like that: The use of earlier problems and the separation of similarity effects.,” J. Exp. Psychol. Learn. Mem. Cogn., vol. 13, no. 4, p. 629, 1987.[42] R. Datta, D. Joshi, J. Li, and J. Z. Wang, “Image Retrieval: Ideas, Influences, and Trends of the New Age,” ACM Comput. Surv., vol. 40, no. 2, pp. 5:1–5:60, 2008.[43] J. M. Martínez, “MPEG-7 Overview (version 10),” ISO/IEC JTC1/SC29/WG11, 2004.[44] S. Committee, “Exchangeable image file format for digital still cameras: Exif version 2.3,” Specif. Camera Imaging Prod. Assoc., vol. 1585, 2010.[45] A. S. Inc., “XMP Specification,” 2012.[46] IPTC, “IPTC Photo Metadata: Core 1.1/Extension 1.1,” 2010.[47] P. Salembier and J. R. Smith, “Overview of multimedia description schemes and schema tools,” Introd. to MPEG-7, pp. 83–93, 2002.[48] K.-S. Goh, E. Y. Chang, and W.-C. Lai, “Multimodal Concept-dependent Active Learning for Image Retrieval,” in Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004, pp. 564–571.[49] C.-H. Hoi and M. R. Lyu, “A Novel Log-based Relevance Feedback Technique in Content-based Image Retrieval,” in Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004, pp. 24–31.[50] X. S. Zhou and T. S. Huang, “Comparing Discriminating Transformations and SVM for Learning During Multimedia Retrieval,” in Proceedings of the Ninth ACM International Conference on Multimedia, 2001, pp. 137–146.[51] Y. Wu, E. Y. Chang, K. C.-C. Chang, and J. R. Smith, “Optimal Multimodal Fusion for Multimedia Data Analysis,” in Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004, pp. 572–579.[52] Y.-Y. Lin, T.-L. Liu, and H.-T. Chen, “Semantic Manifold Learning for Image Retrieval,” in Proceedings of the 13th Annual ACM International Conference on Multimedia, 2005, pp. 249–258.[53] Z. Su, H. Zhang, S. Li, and S. Ma, “Relevance feedback in content-based image retrieval: Bayesian framework, feature subspaces, and progressive learning,” Image Processing, IEEE Transactions on, vol. 12, no. 8. pp. 924–937, 2003.[54] N. Vasconcelos and A. Lippman, “Learning from User Feedback in Image Retrieval Systems.,” in NIPS, 1999, pp. 977–986.[55] F. Jing, M. Li, H.-J. Zhang, and B. Zhang, “An efficient and effective region-based image retrieval framework,” Image Processing, IEEE Transactions on, vol. 13, no. 5. pp. 699–709, 2004.[56] M. A. Conway, S. J. Anderson, S. F. Larsen, C. M. Donnelly, M. A. McDaniel, A. G. R. McClelland, R. E. Rawles, and R. H. Logie, “The formation of flashbulb memories,” Mem. Cognit., vol. 22, no. 3, pp. 326–343, 1994.[57] P. J. Kuo, T. Aoki, and H. Yasuda, “Building Personal Digital Photograph Libraries: An Approach with Ontology-Based MPEG-7 Dozen Dimensional Digital Content Architecture,” in Computer Graphics International Conference, 2004.[58] P.-Y. Chen and P.-J. Kuo, “Archiving of Personal Digital Photograph Collections with a MPEG-7 Based Geotag Related Annotation Methodology,” in Archiving Conference, 2012, vol. 2012, no. 1, pp. 107–110.[59] M. J. L. Pei Jeng Kuo, Po Yen Chen, Yi Ting Wang, Chun Hui Li, “A Ubiquitous Geotag Related Mobile Personal Digital Photograph Annotation System,” in Annual Conference on Engineering & Information Technology, 2014.[60] P. J. Kuo, T. Aoki, and H. Yasuda, “MPEG-7 Based Dozen Dimensional Digital Content Architecture for Semantic Image Retrieval Services,” in Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE’04), 2004.[61] P. J. Kuo, “Continuous Archiving of Personal Digital Photograph Collections with a MPEG-7 Based Dozen Dimensional Digital Content Architecture,” in Proceedings of IS&T Archiving Conference, 2005. 描述 碩士
國立政治大學
資訊科學學系
100753008
103資料來源 http://thesis.lib.nccu.edu.tw/record/#G1007530082 資料類型 thesis dc.contributor.advisor 郭正佩<br>楊立行 zh_TW dc.contributor.advisor Kuo, Pei Jeng<br>Yang, Lee Xieng en_US dc.contributor.author (作者) 李俊輝 zh_TW dc.creator (作者) 李俊輝 zh_TW dc.date (日期) 2014 en_US dc.date.accessioned 2-三月-2015 10:13:38 (UTC+8) - dc.date.available 2-三月-2015 10:13:38 (UTC+8) - dc.date.issued (上傳時間) 2-三月-2015 10:13:38 (UTC+8) - dc.identifier (其他 識別碼) G1007530082 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/73573 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊科學學系 zh_TW dc.description (描述) 100753008 zh_TW dc.description (描述) 103 zh_TW dc.description.abstract (摘要) 生活於數位時代，巨量的個人生命記憶使得人們難以輕易解讀，必須經過檢索或標籤化才可以進一步瞭解背後的意涵。本研究著力個人記憶裡繁瑣及週期性的廣泛事件，進行於「情節記憶語意化」以及「何以權衡大眾與個人資訊」兩議題之探討。透過生命記憶平台裡影像標籤自動化功能，我們以時空資訊為索引提出持續性概念重構模型，整合共同知識、個人近況以及個人偏好三項因素，模擬人們對每張照片下標籤時的認知歷程，改善其廣泛事件上註釋困難。在實驗設計上，實作大眾資訊模型、個人資訊模型以及本研究持續性概念重構模型，並招收九位受試者來剖析其認知歷程以及註釋效率。實驗結果顯示持續性概念重構模型解決了上述大眾與個人兩模型上的極限，即舊地重遊、季節性活動、非延續性活動性質以及資訊邊界註釋上的問題，因此本研究達成其個人生命記憶在廣泛事件之語意標籤自動化示範。 zh_TW dc.description.abstract (摘要) In the digital era, labeling and retrieving are ways to understand the meaning behind a huge amount of lifetime archive. Foucusing on tedious and periodic general events, this study will discuss two issues: (1) the semantics of episodic memory (2) the trade-off between common and personal knowledge. Using the automatic image-tagging technique of lifelong digital archiving system, we propose the Coutinuous Reconceptualization Model which models the cognitive processing of examplar categorization based on temporal-spatial information. Integrating the common knowlegde, current personal life and hobby, the Continuous Reconceptualization Model improves the tagging efficiency. In this experiment, we compare the accuracy of cognitive modeling and tagging efficiency of the three distinct models: the common knowledge model, personal knowledge model and Coutinuous Reconceptualization Model. Nine participants were recruited to label the photos. The results show that the Continous Reconceptualization Model overcomes the limitations inherent in other models, including the auto-tagging problems of modeling certain situations, such as re-visiting places, seasonal activities, noncontinuous activities and information boundary. Consequently, the Continuous Reconceptualization Model demonstrated the efficiency of the automatic image-tagging technique used in the semantic labeling of the general event of personal memory. en_US dc.description.tableofcontents 第一章 緒論 11.1 研究背景與動機 11.2 研究問題與目的 21.3 論文結構 5第二章 生命記憶之文獻回顧 62.1 長期記憶及其特性 72.1.1 長期記憶 72.1.2 脈絡、長期記憶與自傳性記憶 92.1.3 小結 142.2 記憶數位化 152.2.1 個人生命典藏 152.2.2 從記憶朝向回憶 172.2.3 生命記憶之數位模擬與應用 182.2.4 小結 212.3 影像標籤自動化 222.3.1 記憶的表達 222.3.2 影像記憶與檢索 232.3.3 以廣泛或個人知識之描述標籤推薦 252.3.4 小結 262.4 總結 27第三章 持續性概念重構個人化影像標籤系統 293.1 基於空間與時間知識本體 293.2 持續性概念重構模型 323.3 系統架構 373.4 系統功能與介面 38第四章 實驗與評估 404.1 實驗模型說明 404.2 實驗環境 414.3 受試者與指導語 414.4 評估方式 42第五章 結果與討論 445.1 基本資訊 445.2 認知歷程評估 455.3 標籤註釋效率的評估 495.4 跨事件之間標籤相似性評估 515.5 時間與地理相依性標籤相似性評估 535.5 綜合討論 53第六章 結論與展望 56參考文獻 58附錄1 系統介面 63附錄2 地理相依性效率統計表 66附錄3 時間相依性效率統計表 70附錄4 地理相依性標籤相似性詳細表格 77附錄5 時間相依性標籤相似性詳細表格 82附錄6 時間與地理相依性標籤相似性詳細表格 91 zh_TW dc.format.extent 7241605 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1007530082 en_US dc.subject (關鍵詞) 個人生命記憶典藏 zh_TW dc.subject (關鍵詞) 影像標籤自動化 zh_TW dc.subject (關鍵詞) 階層式貝氏網路 zh_TW dc.subject (關鍵詞) 認知模擬 zh_TW dc.subject (關鍵詞) personal archiving en_US dc.subject (關鍵詞) automatic image-tagging en_US dc.subject (關鍵詞) hierarchical bayesian network en_US dc.subject (關鍵詞) cognitive modeling en_US dc.title (題名) 以情境與行為意向分析為基礎之持續性概念重構個人化影像標籤系統 zh_TW dc.title (題名) Continuous Reconceptualization of Personalized Photograph Tagging System Based on Contextuality and Intention en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) [1] D. L. Schacter, The Seven Sins of Memory: How the Mind Forgets and Remembers. Houghton Mifflin Harcourt, 2002.[2] G. Bell, “A personal digital store,” Commun. ACM, vol. 44, pp. 86–91, 2001.[3] J. Gemmell, G. Bell, and R. Lueder, “MyLifeBits: a personal database for everything,” Commun. ACM, vol. 49, no. 1, pp. 88–95, 2006.[4] M. Conway and C. Pleydell-Pearce, “The construction of autobiographical memories in the self-memory system.,” Psychol. Rev., vol. 107, no. 2, pp. 261–288, 2000.[5] E. Berry, N. Kapur, L. Williams, S. Hodges, P. Watson, G. Smyth, J. Srinivasan, R. Smith, B. Wilson, and K. Wood, “The use of a wearable camera, SenseCam, as a pictorial diary to improve autobiographical memory in a patient with limbic encephalitis: a preliminary report.,” Neuropsychol. Rehabil., vol. 17, no. 4–5, pp. 582–601, 2007.[6] J. Liu and P. Dolan, “Personalized news recommendation based on click behavior,” in Proceedings of the 15th, 2010.[7] P. Maglio and R. Barrett, “Intermediaries personalize information streams,” Commun. ACM, vol. 43, no. 8, pp. 96–101, 2000.[8] L. Von Ahn, B. Maurer, C. Mcmillen, D. Abraham, and M. Blum, “reCAPTCHA: Human-Based Character Recognition via Web Security Measures,” Science (80-. )., vol. 321, no. 5895, pp. 1465–1468, 2008.[9] J. Lanier, You are Not a Gadget: A Manifesto. Alfred A. Knopf, 2010.[10] C. G. Bell and J. Gemmell, Total Recall: How the E-Memory Revolution Will Change Everything. Dutton, 2009.[11] L. R. Squire, “Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans.,” Psychol. Rev., vol. 99, no. 2, pp. 195–231, 1992.[12] E. Tulving, “Episodic and semantic memory 1,” Organ. Mem. London Acad., vol. 381, p. e402, 1972.[13] W. James, The Principles of Psychology, no. 第 1 卷. Cosimo, Incorporated, 2007.[14] J.-M. Guyau, “La gen{è}se de l’id{é}e de temps [The origin of the idea of time],” Guyau idea time, pp. 37–90, 1988.[15] T. Ribot, Diseases of memory. Appleton, 1887.[16] E. F. Loftus, Eyewitness testimony. Harvard University Press, 1996.[17] B. K. Jones and D. P. McAdams, “Becoming Generative: Socializing Influences Recalled in Life Stories in Late Midlife,” J. Adult Dev., vol. 20, no. 3, pp. 158–172, Jul. 2013.[18] D. McAdams, “The psychology of life stories.,” Rev. Gen. Psychol., 2001.[19] M. B. Brewer and W. Gardner, “Who is this ‘We’? Levels of collective identity and self representations.,” J. Pers. Soc. Psychol., vol. 71, no. 1, pp. 83–93, 1996.[20] C. C. Marshall, “Challenges and Opportunities for Personal Digital Archiving.”,” Digit. Pers. Collect. Digit. Era, pp. 90–114, 2011.[21] I. Cole, “Human aspects of office filing: Implications for the electronic office,” in Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 1982, vol. 26, no. 1, pp. 59–63.[22] D. Barreau and B. A. Nardi, “Finding and Reminding: File Organization from the Desktop,” SIGCHI Bull., vol. 27, no. 3, pp. 39–43, 1995.[23] D. 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