DOCSLIB.ORG

Signature Redacted Signature Redacted

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Signature Redacted Signature Redacted Efficient Semantic Retrieval on K-Segment Coresets of User Videos by Pramod Kandel S.B., C.S. M.I.T., 2014 Submitted to the Department of Electrical Engineering and Computer Science in Partial Fulfillment of the Requirements for the Degree of Master of Engineering in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology AUgiist, 2015 All rights reserved. Author: Signature redacted Depatiit of Electrical Engineering and Computer Science Aug 3 1, 2015 Certified by: Signature redacted Prof. Daniela Rus, CSAIL Director, Andrew (1956) & Erna Viterbi Professor, Thesis Supervisor Aug 31, 2015 Certified by: Signature redacted Guy Rosman ostd Ooral Associate, Thesis Co-Supervisor Aug 31, 2015 Accepted by: Signature redacted Prui.~ALgrt Me, Chaimj'asters of Engineering Thesis Committee ARCHIVES MASSACHUSETTS INSTITUTE OF TECHNOLOGY JUL 19 2016 LIBRARIES Efficient Semantic Retrieval on K-segment Coresets of User Videos By Pramod Kandel Submitted to the Department of Electrical Engineering and Computer Science Aug 24, 2015 In Partial Fulfillment of the Requirements for the Degree of Master of Engineering in Electrical Engineering and Computer Science ABSTRACT Every day, we collect and store various kinds of data with our modern sensors, phones, cameras, and various gadgets. One of the richest available data is video data. We take numerous hours of videos with our phones and cameras, and store them in computers or cloud. However, because recording videos produce large files, it is hard to search and locate for specific video segments within a video library. We might need the part where "Matt was playing guitar", or we might want to see "the glimpse of John's laptop" among hours of video data that contain those pieces. The goal of this thesis is to create a system that is able to retrieve efficiently the relevant segments(frames) in the video by allowing users to do textual search based on objects of the video, such as "guitar" or "laptop". A big challenge with videos is the huge space required to store them, therefore making it difficult to retrieve and analyze videos. This thesis presents an efficient compression method, which uses k-segment mean coresets to represent the video data using fewer frames while preserving the information content in the original data set. The system then uses a state-of-the-art object detector to analyze and detect objects in the reduced data. The objects and corresponding frames are stored and cross-linked to the original data to enable retrieval. The system allows users to pose text queries about objects in the videos. It is important that the retrieval of the stored objects is as efficient and meaningful as possible. This thesis presents a retrieval algorithm, also based on the k-segment mean coreset algorithm, which allows efficient any-time retrieval of the detected objects, retrieving the "more preferred" or "more important" frames earlier. The system presents the any-time results to the users in an incremental way. This thesis describes the architecture and modules of the objects retrieval system for video data. The modules include the user interface for making the search query and displaying the results, the module for video compression with coresets, the object-detection module, the retrieval module, and the data flow between them. This thesis describes an implementation of this system, the algorithms used, and a suite of experiments to validate and evaluate the algorithms. The results show that using coresets, it is possible to identify, store, and efficiently retrieve video segments by specifying the objects in video data. Page 3 of 107 Page 4 of 107 ACKNOWLEDGEMENTS First and foremost, I would like to thank my thesis supervisor Professor Daniela Rus and my thesis co- supervisor Guy Rosman for guiding me through my Master's program. Prof. Rus has a deep understanding of myriads of topics in the field of robotics and beyond, and has a knack of giving clear and understandable guidelines and comments to her students. Despite her busy schedule, I met her every week, and every meeting with her has positively impacted my understanding on the subject of my thesis and the direction I should be heading. She has shown me the way in the most difficult times. Similarly, Guy has been almost my companion throughout this process, being there to guide and support me at any time I needed him. He is one of the smartest people I have met both in theory and applications of various topics of computer vision, and more generally robotics and computer science as a whole. I am thankful for the opportunity to be supervised by such amazing and smart people. Secondly, my family has always been an inspiration to me. My parents provided for me and sent me to good schools, even when the circumstances were not great for themselves. Their sacrifice at difficult times is the primary reason I'm here and writing this thesis. Similarly, my loving brother Saroj has always been my best friend and has made me smile and laugh when I needed. Thirdly, I thank my close friends who have continuously offered assistance to make my life easier during the thesis write-up process, and have always been there to encourage me. Finally, I am thankful to each and every person I have had opportunity to know during my lifetime. I am confident that each of their positivity and their stories have inspired me to be where I am today, and will keep inspiring and guiding me in days to come. Page 5 of 107 Page 6 of 107 TABLE OF CONTENTS Chapter 1 Introduction...........................................................................................................................18 1.1 Goal........................................................................................................................................... 18 1.2 Challenges................................................................................................................................. 19 1.2.1 Large Data.........................................................................................................................19 1.2.2 Preserving Sem antics on Compression .......................................................................... 20 1.2.3 Object Detection on Videos ............................................ 1 1.2.4 Efficient, Sem antic, and Preferential Retrieval.................................................................21 1.3 Solution Approach .................................................................................................................... 21 1.4 Contributions ............................................................................................................................ 1.4.1 System ............................................................................................................................... 22 1.4.2 Algorithm s ........................................................................................................................ 22 1.4.3 Experiments ...................................................................................................................... 23 Chapter 2 Related W ork ........................................................................................................................ 24 2.1 Life Logging Systems/Diaries ............................................................................................... 24 2.2 Coreset Algorithm s...................................................................................................................26 2.3 Sem antic Retrieval for videos............................................................................................... 27 Chapter 3 Video Summarization and Retrieval: Technical Approach ............................................... 30 3.1 Objects Retrieval System Architecture: Introduction ............................................................ 31 3.2 W eb Interface............................................................................................................................32 Page 7 of 107 3.3 Video Processing ...................................................................................................................... 32 3.3.1 Coreset Tree Creator.........................................................................................................32 3.3.2 Object Detector ................................................................................................................. 33 3.4 Storage ...................................................................................................................................... 33 3.5 Retriever....................................................................................................................................36 Chapter 4 Video to Coreset Tree Creation ......................................................................................... 38 4.1 Coresets: Introduction...............................................................................................................38 4.2 K-segment Mean Coreset Tree Construction (without key frames) .................................... 38 4.3 Sum m arization: Coreset Tree with key frames...................................................................... 39 4.4 Output/Populating inform ation to DB .................................................................................. 41 Chapter 5 Object Detection of Coreset Tree Leaves .......................................................................... 43 5.1 Object Recognition
Load more

Recommended publications
  • Metaverse Roadmap Overview, 2007. 2007
    A Cross-Industry Public Foresight Project Co-Authors Contributing Authors John Smart, Acceleration Studies Foundation Corey Bridges, Multiverse Jamais Cascio, Open the Future Jochen Hummel, Metaversum Jerry Paffendorf, The Electric Sheep Company James Hursthouse, OGSi Randal Moss, American Cancer Society Lead Reviewers Edward Castronova, Indiana University Richard Marks, Sony Computer Entertainment Alexander Macris, Themis Group Rueben Steiger, Millions of Us LEAD SPONSOR FOUNDING PARTNERS Futuring and Innovation Center Graphic Design: FizBit.com accelerating.org metaverseroadmap.org MVR Summit Attendees Distinguished industry leaders, technologists, analysts, and creatives who provided their insights in various 3D web domains. Bridget C. Agabra Project Manager, Metaverse Roadmap Project Patrick Lincoln Director, Computer Science Department, SRI Janna Anderson Dir. of Pew Internet’s Imagining the Internet; Asst. International Prof. of Communications, Elon University Julian Lombardi Architect, Open Croquet; Assistant VP for Tod Antilla Flash Developer, American Cancer Society Academic Services and Technology Support, Office of Information Technology Wagner James Au Blogger, New World Notes; Author, The Making of Second Life, 2008 Richard Marks Creator of the EyeToy camera interface; Director of Special Projects, Sony CEA R&D Jeremy Bailenson Director, Virtual Human Interaction Lab, Stanford University Bob Moore Sociologist, Palo Alto Research Center (PARC), PlayOn project Betsy Book Director of Product Management, Makena Technologies/There;
    [Show full text]
  • Blogging Glossary
    Blogging Glossary Glossary: General Terms Atom: A popular feed format developed as an alternative to RSS. Autocasting: Automated form of podcasting that allows bloggers and blog readers to generate audio versions of text blogs from RSS feeds. Audioblog: A blog where the posts consist mainly of voice recordings sent by mobile phone, sometimes with some short text message added for metadata purposes. (cf. podcasting) Blawg: A law blog. Bleg: An entry in a blog requesting information or contributions. Blog Carnival: A blog article that contains links to other articles covering a specific topic. Most blog carnivals are hosted by a rotating list of frequent contributors to the carnival, and serve to both generate new posts by contributors and highlight new bloggers posting matter in that subject area. Blog client: (weblog client) is software to manage (post, edit) blogs from operating system with no need to launch a web browser. A typical blog client has an editor, a spell-checker and a few more options that simplify content creation and editing. Blog publishing service: A software which is used to create the blog. Some of the most popular are WordPress, Blogger, TypePad, Movable Type and Joomla. Blogger: Person who runs a blog. Also blogger.com, a popular blog hosting web site. Rarely: weblogger. Blogirl: A female blogger Bloggernacle: Blogs written by and for Mormons (a portmanteau of "blog" and "Tabernacle"). Generally refers to faithful Mormon bloggers and sometimes refers to a specific grouping of faithful Mormon bloggers. Bloggies: One of the most popular blog awards. Blogroll: A list of other blogs that a blogger might recommend by providing links to them (usually in a sidebar list).
    [Show full text]
  • Dissertation the Working Narrative
    DISSERTATION THE WORKING NARRATIVE: ANALYSIS OF LINGUISTIC STRUCTURES AND STYLES IN LIFE STORYTELLING ON SOCIAL MEDIA Submitted by Michael Humphrey Department of Journalism and Media Communication In partial fulfillment of the requirements For the Degree of Doctor of Philosophy Colorado State University Fort Collins, Colorado Fall 2017 Doctoral Committee: Advisor: Patrick Plaisance Marilee Long Ashley Anderson Sarah Sloane Kate Mason Copyright by Michael Lee Humphrey 2017 All Rights Reserved ABSTRACT THE WORKING NARRATIVE: ANALYSIS OF LINGUISTIC STRUCTURES AND STYLES IN LIFE STORYTELLING ON SOCIAL MEDIA The stories we tell ourselves, and others, define us. What does that mean when we enter digital life and populate social media networks? In this dissertation, I examine the linguistic structures and styles of content created by people who are specifically prompted to tell a story from their lives. This dissertation focuses on two distinct types of storytelling social media platforms: Cowbird is an self-mediatizing, open site that primes users with life story cues and prompts them to “Tell a story,” while Humans of New York is a filtered, gated-mediatized platform run by one curator who posts pictures and short life narratives on Facebook, Tumblr, his own blog and several other social platforms. I sought to find distinct and/or common narrative structural and stylistic characteristics of the content. Using a combination of Quantitative Content Analysis and Linguistic Inquiry and Word Count (Pennebaker et al., 2007; Pennebaker et al., 2015), this project includes three related studies that begin with basic questions about narrative structures and concludes with two factor analyses of latent linguistic variables.
    [Show full text]
  • The Tech Giant Everyone Is Watching
    Inside Assad’s new Syria America’s Supreme Court swings right Bog-roll Boris, the busted flush How to make meetings less dreadful JUNE 30TH–JULY 6TH 2018 Thetechgiant everyone is watching Contents The Economist June 30th 2018 5 8 The world this week United States 34 The Supreme Court Leaders Right of way 11 Netflixonomics 35 Bureaucracy The tech giant everyone Shuffle up is watching 36 School design 12 America’s Supreme Court Brutalism After Kennedy 36 Immigration policy 12 The war in Syria How we got here The new Palestinians 39 Lexington Brexit and business Amid a 13 Railways India and America row between business leaders Free the rails and Conservative hardliners, a 14 China’s university- The Americas softer Brexit gains political On the cover entrance exam 40 Canada’s climate policy ground, page 21 Netflix has transformed Gaokao gruel Trudeau and the Toronto television. It is beloved by troublemaker investors, consumers and Letters 41 Funerals in Cuba politicians. Can that last? 15 On trade, surveillance Not going gently Leader, page11. The technology, Xinjiang, 41 Brazilian agriculture entertainment industry is football, Brexit Embrapa’s lost sparkle scrabbling to catch up with a disrupter, page18. The 42 Bello internet was meant to make Briefing The high price of political saviours the world a less centralised 18 Netflixonomics place, but the opposite has The television will be happened. Ludwig Siegele revolutionised Special report: explains why it matters, and Fixing the internet what can be done about it. US Supreme Court Justice The ins and outs See our special report after Britain Anthony Kennedy’s retirement After page 42 page 42 21 Business and politics comes at a worrying time: Hard Brexit unravels leader, page12.
    [Show full text]
  • Net Smart When You Put Mto4gjh Profile to Take Control Think About
    Participation rower Net Smart :egy is to dilute it good talk. You unters i -ely in the cybersphere How to Thrive Online when you put Mto4g jh rints and profiles. Create a Google profile to take control world sees when it searches for you.65 Think about wh e , e ches for you; do what's in -'7 your P0 o do abol rints and orofiles. - don't control ) '1 No discussion of digital participation can afford to ignore twitter, tue S unexpected medium that ballooned to hundreds of millions of users. Twit- S ter literacy is a perfect example of how your knowledge of how to use your Howard Rheingold attention, participate and collaborate, and use networks will determine how or whether you use the medium successfully. 11 drawings by Anthony Weeks Twitter Literacy of es Twitter has turned out to be less an inane lifelog of what we ate for lunch and much ii- more a streaming list of cleverly editorialized headlines with links to the main arti- If- cle. For many of us, Twitter is becoming the front page of our morning newspaper. ts, Either in perception or in practice, our reporters are becoming our friends and our friends are becoming the editors of our Twitter-based newspaper. 11- —David Sasaki, "Our Friends Become Curators of Twitter-Based News," 2010 n- he "The role of the internet was critical at the beginning," [Amr] Gharbeia says. "On 'S the 25th, the movements of the protesting groups were arranged in real time through Twitter. Everyone knew where everyone else was walking and we could L'S advise on the locations of blockades and skirmishes with police.
    [Show full text]
  • Risks and Benefits of Emerging Life-Logging Applications November 2011 Final Report – Appendix I
    Risks and benefits of emerging life-logging applications November 2011 Final Report – Appendix I TO L0G OR NOT TO L0G? Risks and benefits of emerging life-logging applications Appendix I Scenario Building and Analysis Template Risks and benefits of emerging life-logging applications 2 Final Report – Appendix I ABOUT ENISA The European Network and Information Security Agency (ENISA) is a European Union (EU) agency which acts as a centre of expertise for the EU Member States and European institutions. It gives advice and recommendations on good practice, and acts as a “switchboard” for exchanging knowledge and information. The agency also facilitates contacts between the European institutions, the Member States, and private business and industry. CONTACT DETAILS The report has been edited by Barbara Daskala. For questions related to this study or to the Emerging Risks Framework, please use the following details: e-mail: [email protected] Internet: http://www.enisa.europa.eu/ Legal notice Notice must be taken that this publication represents the views and interpretations of the authors and editors, unless stated otherwise. This publication should not be construed to be a legal action of ENISA or the ENISA bodies unless adopted pursuant to the ENISA Regulation (EC) No 460/2004 as lastly amended by Regulation (EU) No 580/2011. This publication does not necessarily represent state-of the-art and ENISA may update it from time to time. Third-party sources are quoted as appropriate. ENISA is not responsible for the content of the external sources including external websites referenced in this publication. This publication is intended for information purposes only.
    [Show full text]
  • Digital Object, Digital Subjects
    DIGITAL OBJECTS DIGITAL SUBJECTS Interdisciplinary Perspectives on Capitalism, Labour and Politics in the Age of Big Data Edited by DAVID CHANDLER and CHRISTIAN FUCHS Digital Objects, Digital Subjects: Interdisciplinary Perspectives on Capitalism, Labour and Politics in the Age of Big Data Edited by David Chandler and Christian Fuchs University of Westminster Press www.uwestminsterpress.co.uk Published by University of Westminster Press 101 Cavendish Street London W1W 6UW www.uwestminsterpress.co.uk Text ©the editors and several contributors 2019 First published 2019 Cover: Diana Jarvis Printed in the UK by Lightning Source Ltd. Print and digital versions typeset by Siliconchips Services Ltd. ISBN (Hardback): 978-1-912656-08-0 ISBN (PDF): 978-1-912656-09-7 ISBN (EPUB): 978-1-912656-10-3 ISBN (Kindle): 978-1-912656-11-0 ISBN (Paperback): 978-1-912656-20-2 DOI: https://doi.org/10.16997/book29 This work is licensed under the Creative Commons Attribution-NonCommercial- NoDerivatives 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA. This license allows for copying and distributing the work, providing author attribution is clearly stated, that you are not using the material for commercial purposes, and that modified versions are not distributed. The full text of this book has been peer-reviewed to ensure high academic standards. For full review policies, see: http://www.uwestminsterpress.co.uk/ site/publish. Competing Interests: the editors and contributors declare that they have no competing interests in publishing this book Suggested citation: Chandler, D.
    [Show full text]
  • Contextual Social Networking
    Technische Universit¨atM¨unchen Fakult¨atf¨urInformatik Contextual Social Networking Dipl.-Phys., Dipl.-Inform. Dr.rer.nat. Georg Groh Habilitationsschrift Mitglieder des Habilitationskomittees: Prof. Dr. Johann Schlichter Prof. Dr. Bettina Berendt Prof. Dr. Helmut Seidl Kurz-Zusammenfassung Der zentrale Gegenstand der vorliegenden Arbeit ist die vielschichtige Frage, wie Kontexte detektiert und abgeleitet werden k¨onnen,die dazu dienen k¨onnen,neuar- tige kontextbewusste Social Networking Dienste zu schaffen und bestehende Di- enste in ihrem Nutzwert zu verbessern. Die (noch nicht abgeschlossene) erfolgre- iche Umsetzung dieses Programmes f¨uhrtauf ein Konzept, das man als Contextual Social Networking bezeichnen kann. In einem grundlegenden ersten Teil werden die eng zusammenh¨angendenGebiete Contextual Social Networking, Mobile Social Networking und Decentralized Social Networking mit verschiedenen Methoden und unter Fokussierung auf verschiedene Detail-Aspekte n¨aherbeleuchtet und in Zusam- menhang gesetzt. Ein zweiter Teil behandelt die Frage, wie soziale Kurzzeit- und Langzeit-Kontexte als f¨urdas Social Networking besonders interessante Formen von Kontext gemessen und abgeleitet werden k¨onnen. Ein Fokus liegt hierbei auf NLP Methoden zur Charakterisierung sozialer Beziehungen als einer typischen Form von sozialem Langzeit-Kontext. Ein weiterer Schwerpunkt liegt auf Methoden aus dem Mobile Social Signal Processing zur Ableitung sinnvoller sozialer Kurzzeit-Kontexte auf der Basis von Interaktionsgeometrien und Audio-Daten. Es wird ferner unter- sucht, wie pers¨onliche soziale Agenten Kontext-Elemente verschiedener Abstraktion- sgrade miteinander kombinieren k¨onnen.Der dritte Teil behandelt neuartige und verbesserte Konzepte f¨urkontextbewusste Social Networking Dienste. Es werden spezielle Formen von Awareness Diensten, neue Formen von sozialem Information Retrieval, Konzepte f¨urkontextbewusstes Privacy Management und Dienste und Plattformen zur Unterst¨utzungvon Open Innovation und Kreativit¨atuntersucht und vorgestellt.
    [Show full text]
  • Automatically Augmenting Lifelog Events Using Pervasively Generated Content from Millions of People
    Sensors 2010, 10, 1423 - 1446; doi:10.3390/100301423 OPEN ACCESS sensors ISSN 1424-8220 www.mdpi.com/journal/sensors Article Automatically Augmenting Lifelog Events Using Pervasively Generated Content from Millions of People Aiden R. Doherty ? and Alan F. Smeaton Centre for Sensor Web Technologies, Dublin City University, Glasnevin, Dublin 9, Ireland; E-Mail: [email protected] Received: 24 December 2009; in revised form: 19 January 2010 / Accepted: 3 February 2010 / Published: 26 February Abstract: In sensor research we take advantage of additional contextual sensor information to disambiguate potentially erroneous sensor readings or to make better informed decisions on a single sensor’s output. This use of additional information reinforces, validates, semantically enriches, and augments sensed data. Lifelog data is challenging to augment, as it tracks one’s life with many images including the places they go, making it non-trivial to find associated sources of information. We investigate realising the goal of pervasive user-generated content based on sensors, by augmenting passive visual lifelogs with “Web 2.0” content collected by millions of other individuals. Keywords: lifelogging; event augmentation; SenseCam; Web 2.0 1. Introduction Almost everything we do these days is in some way monitored, sensed, or logged. We’ve come to accept—or maybe we just ignore—this massive surveillance of our lives from a variety of sensors because it brings us benefits. For example, we have a more secure feeling when we know there is CCTV present, we get itemised billing of our phone usage from phone companies, and we get convenience and even loyalty bonuses as a result of some of our regular store purchases.
    [Show full text]
  • 544506-00091.Pdf (209.58
    PRIVACY, FREE SPEECH, AND “BLURRY- EDGED” SOCIAL NETWORKS Lauren Gelman* Abstract: Much of Internet-related scholarship over the past ten years has focused on the enormous benefits that come from eliminating interme- diaries and allowing user generated one-to-many (one person to many people) communications. Many commentators have noted the tension created between the positive benefits for free speech and the negative ef- fects on user privacy. This tension has been exacerbated by technologies that permit users to create social networks with “blurry edges” —places where they post information generally intended for a small network of friends and family, but which is left available to the whole world to access. The thought is that someone the user cannot identify a priori might find the information interesting or useful. These technological advances have created enormous benefits as people connect to each other and build communities online. The technology that enables these communities, however, also creates an illusion of privacy and control that the law fails to recognize. This Article discusses the technological, social, and legal re- gimes that have created this framework, and proposes a technical solution to permit users to maintain networks with blurry edges while still appro- priately balancing speech and privacy concerns. Introduction One of the many important aspects of the Internet is the “many-to- many” communication it enables—allowing individuals to distribute a message to many recipients at once.1 For the first time in history, the economics of publishing place the individual speaker on even ground * © 2009, Lauren Gelman. Lauren Gelman served as Executive Director of Stanford Law School’s Center for Internet and Society and a Lecturer in Law at Stanford Law School until June 2009.
    [Show full text]
  • Blogs in Education Kevin Curran and David Marshall School of Computing and Intelligent Systems, Faculty of Engineering, University of Ulster
    3515 Kevin Curran et al./ Elixir Adv. Engg. Info. 36 (2011) 3515-3518 Available online at www.elixirjournal.org Advanced Engineering Informatics Elixir Adv. Engg. Info. 36 (2011) 3515 -3518 Blogs in education Kevin Curran and David Marshall School of Computing and Intelligent Systems, Faculty of Engineering, University of Ulster. ARTICLE INFO ABSTRACT Article history: Educational blogs are used to allow educators to interact with students from any location. Received: 18 May 2011; Teachers sharing ideas through blogs is a promising way to communicate teaching ideas and Received in revised form: allows multicultural teaching methods to be disseminated. The blogs that tell the educator 8 July 2011; how to use technology within the classroom are informative as many teachers would have no Accepted: 18 July 2011; idea about such teaching methods. Research based blogs allow users to see different educational topics discussed in more depth. This paper provides an overview of the impact Keywords blogs are having in an educational context. Educational blogs, © 2011 Elixir All rights reserved. Classroom, Teachers. Introduction Xanga, started in 1996, had only 100 diaries by 1997, and over A blog is a website that is maintained by an individual or 50,000,000 in December 2005. It was the launch of Open group with regular updates of information; this information Diaries in 1998 that helped blogging become more popular, as could include diary entries, descriptions of events or in this case this was the first blog community where readers could add educational material. In most blogs readers can supply comments to other writers' blog entries.
    [Show full text]
  • Lifelogging: Personal Big Data
    Full text available at: http://dx.doi.org/10.1561/1500000033 LifeLogging: Personal Big Data Cathal Gurrin Insight Centre for Data Analytics Dublin City University [email protected] Alan F. Smeaton Insight Centre for Data Analytics Dublin City University [email protected] Aiden R. Doherty Nuffield Department of Population Health University of Oxford [email protected] Boston — Delft Full text available at: http://dx.doi.org/10.1561/1500000033 Foundations and Trends R in Information Retrieval Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is C. Gurrin, A. F. Smeaton, and A. R. Doherty. LifeLogging: Personal Big Data. Foundations and Trends R in Information Retrieval, vol. 8, no. 1, pp. 1–107, 2014. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-60198-803-4 c 2014 C. Gurrin, A. F. Smeaton, and A. R. Doherty All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Cen- ter, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC).
    [Show full text]