I Minds2009 Future Media Prof Rik Van De Walle (Ibbt Mm Lab U Gent)


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I Minds2009 Future Media Prof Rik Van De Walle (Ibbt Mm Lab U Gent)

  1. 1. Future MEDIA
  2. 2. Overview What is this about? Future media - evolutions and trends Some key trends Resulting research challenges / plans Achievements so far a lot of projects: please see IBBT website... spin-off companies & patents other 2
  3. 3. Future media – evolutions and trends Approaching the ‘Zettabyte Era’ by 2012, annual global IP traffic will exceed half a zettabyte, of which 90% will be video traffic mobile data traffic will double each year Super Hi-Vision or UDTV (Ultra High Definition Video) 7680 4320 pixels Japan plans to deploy UDTV broadcasting in 2015 requires ca. 600 Mbit/s with current technologies 3
  4. 4. Future media – evolutions and trends Emerging high-definition user-generated content multiple versions of online content (e.g., YouTube) soon to be consumed on high-resolution displays need for on-the-fly adaptation Managing huge content collections automatic detection of concepts interactive semantic search multi-modal analysis and retrieval algorithms multimedia exploration systems 4
  5. 5. Future media – evolutions and trends Recognition of many object classes, scalable in the number of classes (both for training and at run-time) Limit the need for supervision 5
  6. 6. Future media – evolutions and trends Exploit context information (scene, other objects, geometry, …) Couple textual descriptions to image content (nouns- objects, adjectives-attributes, verbs-actions) and exploit text to provide contextual information 6
  7. 7. Future media – evolutions and trends Distributed smart camera systems multi-camera analysis, embedded and distributed processing applications connect to general purpose video analysis services applications concentrate on high-level aspects; camera system handles low-level and access control privacy issues
  8. 8. Future media – evolutions and trends In the brain regions always connect bi-directionally, in computer vision recognition all too often is the endpoint of a one-way bottom-up pipeline. Recognition has a pivotal role to play in terms of motion analysis, 3D reconstruction, inpainting, ... We need recognition to talk to all kinds of complementary visual processes. We even contend that a lot of progress in these other areas could actually come from recognition, rather than from further refinements along the current lines of thinking 8
  9. 9. Future media – evolutions and trends Applications based on recognition automatic resizing 3D city reconstruction traffic safety content-based image retrieval 9
  10. 10. Future media – evolutions and trends Applications based on recognition video summarization virtual editors surveillance … 10
  11. 11. Future media – evolutions and trends HCI - interactive 3D environments natural and intuitive interaction techniques for emerging environments ‘serious games’ (education, therapy, ...) Video surveillance cameras are being installed virtually everywhere video analysis as security sensor intuitive control room applications combining all event information 11
  12. 12. Future media – evolutions and trends Mobile and context-sensitive interactive systems 12
  13. 13. Future media – evolutions and trends Multi-modal interaction in 3D and virtual environments 13
  14. 14. Future media – evolutions and trends Interactive workspaces 14
  15. 15. Future media – evolutions and trends User-centered software engineering 15
  16. 16. Future media – evolutions and trends Computer graphics and computer animation modeling, rendering and animation video-based CG and animation stylized drawn animation volume rendering and information visualisation Physically based illumination simulation for virtual Real-time photo-realistic hair prototyping and skin for games and movie special effects Image based modeling and rendering for real world objects/subjects/scenes 16
  17. 17. In conclusion: some KEY TRENDS Zillions of data need for efficient indexing mechanisms Different platforms content reformatting User-generated content, interactivity semantic-level interaction with video content multimodal data and multimodal interaction Uncontrolled environments increased robustness better generalization 17
  18. 18. In conclusion: some KEY TRENDS Towards cognitive image understanding increase number of categories reduce level of supervision integrate cognitive information in other image processing tasks global reasoning: relations, context, ... modular systems "In 10 years we will have the first systems that can interpret a never seen photo or video and that can be put into an unknown environment and react intelligently" 18
  19. 19. Resulting research challenges Advanced video coding coding techniques for very high resolutions e.g., characteristics of 16x16 pixels 360p 720p 2360p increasing coding efficiency without increasing computational complexity (too much) 19
  20. 20. Resulting research challenges New coding paradigm: Distributed Video Coding mobile video applications multi-view video entertainment visual sensor networks wireless video cameras wireless low-power surveillance 20
  21. 21. Resulting research challenges Scalable graphics MESHGRID 21
  22. 22. Resulting research challenges Scalable graphics wavelet-based approach 22
  23. 23. Resulting research challenges Scalable graphics move towards real-world applications design, architecture virtual reality cartography education, entertainment nedicine, modeling 23
  24. 24. Resulting research challenges Long-term goal adaptation and delivery framework for personalized and immersive interactive multimedia experiences super HD / 3D Immersive Multimedia Experience (“rollercoaster experience”) sensory effects Annotation Universal Multimedia Experience Retrieval Adaptation Universal Multimedia Access Delivery 24
  25. 25. Resulting research challenges Content adaptation and transcoding HDTV originally acquired high definition material SDTV Mobile (iPod) legacy applications semantically repurposed common pan/scan editing (AVID)
  26. 26. Resulting research challenges Transform low-resolution rubbish into high-resolution content (first steps…) original (4x) SR (4x)
  27. 27. Resulting research challenges Multimedia data analysis and feature extraction texture detection and classification content-based multimedia information retrieval multi-camera video surveillance object detection and tracking immersive control rooms 27
  28. 28. Future media – evolutions and trends Camera selection: Making sense of the information overload
  29. 29. Future media – evolutions and trends Stitching: making sense of it captured data
  30. 30. Resulting research challenges Metadata technology and exploitation semantic web technology W3C activities on media annotation Open Linked Data linking external domain knowledge enable reasoning 30
  31. 31. Resulting research challenges Metadata technology for media production metadata is much more than ‘data about media objects’ pursue model-driven product development better communication: between staff and machines during acquisition (associating audiovisual material) for editing and repurposing (automate production tasks) 31
  32. 32. Resulting research challenges Computer Graphics Video/film + Scene Editing and Interaction + Ease of capture and visualisation Add / remove / clone objects Film with camera Change shape / appearance / lighting Project on screen Animation + Film “language” well understood Interaction / Navigation - Synthetic 3D models - Scene editing difficult, no navigation/interaction as in realistic modelling is a painstaking task CG. Video-Based Computer Graphics bridges the gap (multi-view video as shape & appearance primitive in CG)
  33. 33. Resulting research challenges Architectures supporting massive multi-user, multi-platform scalable networked multimedia (virtual communities, gaming, networked virtual environments, …) NVEIP server(s)
  34. 34. Resulting research challenges Game technology efficient production tools (e.g., digital sculpting) real-time interaction with environment (physics) 34
  35. 35. Resulting research challenges Application domains: virtual communities, gaming, networked virtual environments, … Research topics: scalability issues scalability assessment
  36. 36. Resulting research challenges Network intelligence Error resilience Error concealment
  37. 37. Resulting research challenges Media-aware security and authentication watermarking fingerprinting content authentication Applications control of quality, legitimacy and authenticity of content disclosure of digital archives content distribution control art authentication and dating 37
  39. 39. Achievements - spin-off companies Androme Voice and video over IP solutions iDTV computer graphics&animation networked virtual environments aQuartic media streaming environment metadata handling and exploitation semantic web technologies (RDF, OWL) content adaptation software platform (‘NinSuna’) 39
  40. 40. Achievements - spin-off companies Eyetronics systems & services for 3D scanning high quality flexible & efficient scanning main applications: gaming & film production GeoAutomation 3D acquisition of structural information in cities based on mobile mapping (vehicle & cameras) main application: digital surveying 40
  41. 41. Achievements - spin-off companies QuESD sports and video analysis systems access control systems, including embedded devices and video streaming solutions eSaturnus digital image acquisition & rendering main applications: supporting surgery & endoscopy 41
  42. 42. Achievements - patents Patents active patent policy while NOT excluding open-source approach! some numbers: 5 granted 3 pending 42
  43. 43. Achievements - other Strong participation in standardization still image coding: JPEG video coding: MPEG / VCEG / VQEG semantic web: W3C A lot of contract research bilateral various projects (EU, IWT, ...) Strong collaboration with a lot of recognized research partners 43
  44. 44. Contact info IBBT Offices Zuiderpoort Office Park Gaston Crommenlaan 8 (bus 102) B-9050 Gent-Ledeberg Belgium t: +32 9 331 48 00 f: +32 9 331 48 05 e: info@ibbt.be Or even better: just talk to one of us during iMinds 44