Weaving the Visual Web Ramesh Jain Dept. of Computer Science University of California, Irvine [email protected] .
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Weaving the Visual Web
Ramesh Jain Dept. of Computer Science
University of California, Irvine [email protected]
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• Memories of experiences.
• Explicit contextual communicaFon. – Data is a new uFlity. – Text is too abstract in many situaFons.
Duality of Photos
Why do we take photos?
Where do photos come from?
• Drawings • Pain6ngs • Cameras • Smart Cameras • Graphics
Camera History
The Role of Photos con6nues to Evolve
• Memory • Informa6on
– Notes – Documenta6on
• Ephemeral
Photos have ‘half life’!
In 20th century, we tolerated photos in our textual documents.
In 21st century, you create visual documents that tolerate text.
Major Disruption in Photos: From Memories to Information Sources.
Photos are the most compelling source of information.
Experiences
Life =
Events
+
Progress: Knowledge Creation and Propagation
Visual
Visual knowledge
Oral
Oral knowledge
Textual knowledge
Berners-‐Lee: Suppose all the informa6on stored on computers everywhere were linked. Suppose I could program my computer to create a space in which anything could be linked to anything.
Web: Human experiences, knowledge, and understanding captured using associative links in DOCUMENTS.
Text based documents are not NATURAL. Language and Literacy come in the way.
Imagine if every photo and video captured were connected to every other! And to other information!!
What is a camera?
Captures intensity from a point in the world.
Is a Smartphone camera sFll a camera?
Many sensors capture metadata related to the moment and capture. • Exposure Time • Aperture Diameter • Flash • Metering Mode • ISO Ratings • Focal Length • Time • Location • Face
Smartphone camera captures events.
Computa6onal Representa6on of an event.
Experien6al Data: • Photos • Video • Audio • Accelerometer • Heart rate • …
EMPT: Extractable Mobile Photo Tags
Exif
Content Analysis
EMPT
People Place Objects Events
…
Krumbs: Capture and Connect holisFc experience of a moment.
What: Objects Who: People When: Events Where: Location Why: Intent/Emotions
All photos and associated context
is automatically
Organized in a Web, and
Shared (if desired).
Duality of Photos: Relevance to MM and CompuFng
• Memories: Search and Retrieval
• InformaFon communicaFon: Web, Big Data
How do you search photos?
What Who When Where Why
AssociaFons related to these.
Searching ‘For a Photo’ and
Searching ‘From a Photo’.
28
29
30
Who When Where What Why
AssociaFons related to these.
Marking Moments: Micro Blogs
• Facebook Status and Tweets started Micro Blogs. – Now there are many – Instagram, Snapchat, …
• Problem with Tweets: More Noise less Data.
• Time to add Focused Micro Blogs – Sensors – Importance of marking a moment
Waze
Crowdsourced SituaFons
Crowdsourced SituaFons
A Photo is a Click in Real World.
• Remember Kodak Moment! • For each photo:
• Unique ID, • All metadata of the event, • Tags, • Links, • AnnotaFons.
Crowdsourced SituaFons
At 435 Main 8:37 AM
10/20/15 37
10/20/15 38
Flood level - Shelter
Flood Level Shelter
Classify (Flood level - Shelter)
Krumbs Used as Focused Micro Blog
• One Click upload to the FMB-‐App Server. • The client sends:
– Sender ID – Photo – GPS and Place – Time and Event – Emoji based Context and annota6on – Any addi6onal comments
• As JSON
FMB-‐App Server
• FMB-‐App Server uses EventShop for appropriate aggrega6ons. – Loca6on – Geographic area (ward, town, city, …) – Also computes some rates of changes. – Determines Trends – Classifies areas based on evolving and current situa6ons.
• Allows drill-‐down to show even individual photos.
Tweets VS Krumbs
Tweets 1. Tweet require thinking and
typing. 2. Loca6on of a tweet and the
corresponding event may be different.
3. Tweets are subjec6ve.
Krumbs 1. Krumbs have more
informa6on and are spontaneous.
2. Krumbs maintains event loca6on.
3. Krumbs are objec6ve.
Seman6c Links for a Photo
• Photo Level – Automa6c crea6on – Manual Annota6on – Manual Crea6on
• Segment Level – Automa6c Crea6on – Manual Crea6on
ObjecFve Self: From Personal Big Data
Life Events relate disparate streams to life.
Personal photos on smart phones TELL a lot about you.
Visual Web PlaZorm
Contextual Reasoning and Event ComputaFons
NavigaFon and Search
Krumbs
Next App
Knowledge Discovery: Event AnalyFcs and VisualizaFon
Agro-‐ Tech
Clean India Personal
Sharing and CommunicaFon
Your Personal Visual Web on Smartphone
Photo Cloud
Moment Capture
Contextual Reasoning and
Event ComputaFons
Event AnalyFcs And VisualizaFon
NavigaFon and Search
• Available on Android and iOS.
• Your data remains on your phone unless shared.
Sharing
Developing An App: Agro-‐Tech
Contextual Reasoning and Event ComputaFons
NavigaFon and Search
Krumbs for Agro-‐Tech
Agro Knowledge Discovery: Event AnalyFcs and VisualizaFon
Agro-‐ Tech
Sharing and CommunicaFon
Popular Selfie Food Agriculture Shopping
Technology for Building Visual Web
• Visual Authoring Environment: HTML for Visual Data.
• Content Analysis • Deep Contextual Reasoning: From Smartphones, sensors, IoT, personal history, social, personal and all other events.
• Event Clustering and recogniFon. • Photo Ranking • Combine with Deep Learning based Content Analysis
• Visual NavigaFon • Cross sharing and integraFon with other PlaZorms. • Combine Algorithmic and InteracFve tools.
For Visual Web, we need • Addressing (URI) • Transfer Protocol (HTTP) • Authoring and Presentation (HTML) • Ranking • Contextual Processing • Content Analysis • Privacy and Security • Information Vs Experience
Challenges
Sky is the Limit. ApplicaFons:
Lifestyle Health
Commerce Surveillance and Monitoring
Agriculture Research and development
ConstrucFon …
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