Elearning - Rich Media Search

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As multimedia are being used to facilitate and enhance teaching and creative learning, making rich media including images and videos searchable are critical in today and future elearning platform and management system. Traditionally, it's a difficult challenge. Some of the team members have invented an interdisciplinary framework which integrates the state-of-the-art image recognition technology and brain science research from MIT, intelligent cluster algorithm and patentable digital “tagging” technology

Tecnología Educación

OMNIMEDIA “Intelligent Rich Media Search Platform”

Searchable Media for E-Learning ,[object Object]

OMNIMedia Innovation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Why better? Accuracy Hand inserted metadata Cost effectiveness Machine learning / Computer Vision OMNIMedia Platform

Features highlights ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Object detection Cardeal.com Bookmark the Info without Leaving the video

Youtube Video NYC Tiffany Bookmark the Info without Leaving the video

Object detection Great Sushi from Porter Sq, Cambridge Bookmark the Info without Leaving the video

Image Recognition Input image Texture Based Classification Tree / Not-Tree Classification Feature Vector Decision Input Image Shape Based Classification car car ped Biological Model Feature Extraction Car / Not-Car Classification Feature Vector Decision

Image Recognition Performance Biological Model

Auto-tagging for photographs ,[object Object],[object Object],[object Object],[object Object]

Clustering – add contextual info http://eigencluster.csail.mit.edu/

Interdisciplinary framework (hybrid solution) OMNIMedia Cluster Algorithm OMNIMedia platform Auto-generate Initial Metadata Add contextual Info to further enhance metadata User enriched Media content Metadata – fine Tune the image Recognition engine Computer Vision (Image recognition)

Online Content Delivery Stack MySpace Operating System Browser ??? MLB.com YouTube etc G o o g l e WWW Internet

Online Content Delivery Stack Semantic Web / Metadata layer Internet OS (Browser and OS converge) Search www Internet G o o g l e OMNIMedia MySpace MLB.com YouTube etc ?

Technology Diffusion Web 2.0 services -> applications on InternetOS Data-driven G o o g l e OMNIMedia

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Elearning - Rich Media Search

1. OMNIMEDIA “Intelligent Rich Media Search Platform”

6. Why better? Accuracy Hand inserted metadata Cost effectiveness Machine learning / Computer Vision OMNIMedia Platform

8. Example: MLB.com

9. Object detection Cardeal.com Bookmark the Info without Leaving the video

10. Youtube Video NYC Tiffany Bookmark the Info without Leaving the video

11. Object detection Great Sushi from Porter Sq, Cambridge Bookmark the Info without Leaving the video

12. Technology & Product

13. Image Recognition Input image Texture Based Classification Tree / Not-Tree Classification Feature Vector Decision Input Image Shape Based Classification car car ped Biological Model Feature Extraction Car / Not-Car Classification Feature Vector Decision

14. Image Recognition Performance Biological Model

15.

16. Tagging assist

17. Clustering – add contextual info http://eigencluster.csail.mit.edu/

18. Interdisciplinary framework (hybrid solution) OMNIMedia Cluster Algorithm OMNIMedia platform Auto-generate Initial Metadata Add contextual Info to further enhance metadata User enriched Media content Metadata – fine Tune the image Recognition engine Computer Vision (Image recognition)

19. Online Content Delivery Stack MySpace Operating System Browser ??? MLB.com YouTube etc G o o g l e WWW Internet

20. Online Content Delivery Stack Semantic Web / Metadata layer Internet OS (Browser and OS converge) Search www Internet G o o g l e OMNIMedia MySpace MLB.com YouTube etc ?

21. Technology Diffusion Web 2.0 services -> applications on InternetOS Data-driven G o o g l e OMNIMedia

22. Value Chain

Notas del editor

Searchable video stream Non-linear video content access Crawlable - Video content -> text -> publish to web and crawled by search engine such as Google (and use Search Optimization technique) Dynamic - insert Ad (use image detection to detect sponsor images (e.g. ketchup) and dynamically insert link inside the video) Linkable - insert link (from one region of a frame in a clip to another frame in another clip – hypermedia) Unobtrusive - insert Text Ads to the clip on the side instead of a short clip at the opening

Elearning - Rich Media Search

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