Semi-automatic and easy creation of learning friendly OCW video content


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This was one of the posters at the OCWC Global 2011 meeting. Modified as ppt file to be uploaded here.

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Semi-automatic and easy creation of learning friendly OCW video content

  1. 1. OCWC Global meeting 2011Semi-automatic and easy creation oflearning friendly OCW video content CSatoshi SHIMADA1, TadashiNAKANISHI1, Akira KOJIMA1and Y hi i FUKUHARA d Yoshimi 2 1NTT Cyber Solutions Laboratories 2Meiji University y j y
  2. 2. MotivationCreating a learning-friendly edited video, for video sharing g g y , gon the web, is painful and time-consuming. Take time Good skills required Costs moneyHow to make this process easy?At the same time how to make edited video learning time,friendly ?The goal is to automatically extract information from alecture video and use them to produce a better version ofthe video.
  3. 3. ProblemWe need to take a video and edit it.The cost of video capture can be reduced by fix HD camera.Wide angle HD camera can record whole of lecture. However, HD video is not suitable for sharing on the Web. , gBecause, (1)File size of HD video is too large (2)Slide in simple downsizing video is i unreadable d bl (3)The entire scene is boring ( ) Video captured by fixed cameraVideo editing manually takes much time time.
  4. 4. Proposed method Proposed methodProposed workflow for the easy and better creation Cature the entire scene to a video birds-eye view by Full HD camera Video file is moved to Laptop Automatic detection of important Information Semi-automatic S Screen/Speaker/Slide change /Sp a /S a g transformation Post-production Post production (Mixing) Screen + Speaker + Slide change information produced video
  5. 5. Principle 1920 pixels i l- speaker- Screen or black board- atmosphere of hallare assembled based on 1080 pixelsediting template-projection di t ti of screen j ti distortion f-brightness of speaker brightness Editing template A Editing template B Editi t l t are corrected corrected. 720 pixels 400 pixels i l
  6. 6. Video processing Video processing(1)Speaker detection find faces in the image detection: linear Interpolation is conducted for no face image(2) SScreen d t ti detection: fi d a rectangle under appropriate find t l d i t conditions, size and vertex angle diti i d t l Because th camera can b positioned almost everywhere B the be iti d l t h in the lecture room a homography is used to map the room, screen coordinates to a flat rectangle as if it was seen from the front of it it.(3) Chaptering: Based on a subtraction method upon N equidistant frames to determine if a ‘Slide change’ has occurred or not in ‘Screen region’ S
  7. 7. Usability evaluation15 Participants without prior knowledge were asked howthey reviewed the p y post-processed video in comparison p pawith the original one. gVideos used: 4(=20min×2, 1hour×2) ,720×408 pixels Comparison of M C i f Mean O i i S Opinion Score Original video Proposed method Original video(simple down conversion) S Screen visibility y Speaker visibility Not boring g Presence Overall impressionPostP t processed video d id for learning use 1 2 3 4 5by the proposed method bad good
  8. 8. Other example Other example Original id O i i l videoFacial search area Screen area set by manually Post processed video by the proposed method at the b i of l h begin f lecture at the middle of l h iddl f lecture
  9. 9. Video sharing on the Web Video sharing on the Web Enhance the video sharing function by using SceneKnowledge, which provides a user-friendly web interface to view videos, annotate them and post comment. Post-produced P t d d lecture video AnnotationChapter is displayed within a certain chapter of theComment input form video SceneKnowledge: A Video scene-based video sharing and comment posting system
  10. 10. How to use our software How to use our softwareSceneEditor is a client software implementing the proposed method.Minimum operation is as follows1.1 determine the editing duration2. Set facial search area3. Set clipping area of speaker4. detect screen a a . area5. select or set an editing template g p6. comand video procressing --- auto processing ---Time required for automated post-production is; post production Roughly correspond to the time of the video itself
  11. 11. Empowering communities with ICT Innovation SceneKnowledge: A Video-based Knowledge Sharing System Know-how Know how extraction by scene-based video sharing scene based Overview Utilizing video: SceneKnowledge Collective knowledgeA wide variety of knowledge and know-how is being lost due to changes in the structure stored by participantsof households coupled with Japans low birth rate and ageing population. Although Japan s Video Vid contentt t writing comments andefforts are being made to preserve this heritage in video records, people do not obtain Q&A responses makes movementsknowledge just by watching videos. Our proposed system splits video content into and situations easy Comments are linkedmanageable units so that the corresponding knowledge and know-how can be know how to understand to videos allowing videos,discovered and shared more easily. This system can be accessed remotely on PCs and users to quickly accessmobile terminals, allowing information to be shared widely in everyday situations and other scenes of interest to themproviding a useful tool for lifelong learning and for invigorating communities communities. Points reinforced by visual Features annotation New findings are encouraged by■ By watching in scene units it is possible to collect useful on topic comments. units, on-topic comments comparing with i ith■ Users can search the comments to quickly discover other scenes of interest to them. appended videos■ New discoveries can be made by comparing comments, attached videos etc..■ Can also be accessed on mobile phones and touch-screen smartphones. Can be accessed Lecture video slides anywhere by mobile■ The optional Scene Editor tool incorporates lecture video material from universities phones or and lecturer extracted and the like to produce polished results results. smartphones and neatly arranged Application scenarios Can also be used for scene listings g■ To support e learning aimed at improving sports skills or technical ability*¹ e-learning Video analysis: Vk video handling library or for digest■ As a forum for the sharing and exchange of knowledge within communities*² ーー playback ーー■ As a forum for review and lifelong learning tied in with the delivery of university g g y y ーー ーー ーー Long videos cover L id ーー lectures*³ a mixture of many■ As an in-house sharing site for corporate training and technology transfer different topics Indexes are added by video■ As a system for archiving important video content and summarized video clips analysis to make the content easier to grasp*1 Tests conducted jointly with NTT Knowledge Square “N-Academy”*2 Tests conducted jointly with Sakuho Town “Farming community support technology”*3 Joint study with Keio University “JOCW” 3 JOCWContact: Copyright © 2011 NTT. All Rights Reserved.