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What is Media in MIT Media Lab, Why 'Camera Culture'

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'Media' is a plural for medium. The medium for impact of digital technologies at MIT Media Lab can be photons, electrons, neurons, atoms, cells, musical notes and more.

Over the last 40 years, computing has moved from processor, network, social and more sensory.

MIT Media Lab works at the intersection of computing and such media for human-centric technologies.

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What is Media in MIT Media Lab, Why 'Camera Culture'

  1. 1. Why ‘Media’ in MIT Media Lab Why ‘Camera Culture’ Ramesh Raskar, Asso. Prof., Camera Culture, MIT Media Lab
  2. 2. Processor Network + Processor People + Network + Processor Computing Internet Computing Social Computing
  3. 3. Processor Network + Processor People + Network + Processor Senses , I/o + People + Network + Processor Computing Internet Computing Social Computing Sensory Social Computing Augmented Social Computing Process Human NW Sense Visual Social Computing
  4. 4. Bits Photons Co-Media Lab Computing Internet Computing Social Computing Sensory Social Computing Augmented Social Computing
  5. 5. Emerging Worlds Emerging Tech Predictable World Predictable Tech M_L: last 30 years M_LABx: next 30 years
  6. 6. Camera Culture: Motivating Questions • What will a camera/display look like in 20 years? • How will the next billion cameras change the social culture? • How can we augment the camera to support best ‘image search’? • How will portable health diagnostics impact healthcare? • Will we live mostly in virtual/augmented reality, telepresent? – TiVo for life? • How will ultra-high-speed/resolution imaging change us? • How can we improve ‘trust’ in imaging? • Can we print anything .. Cars, food, .. babies .. – (what will make Amazon obsolete) • What are the opportunities in pervasive recording? – e.g. GoogleEarth Live • What will be in Photoshop2030? • What is the future of movie-making, news reporting, sports viewing?
  7. 7. Bits PhotonHacking Computer Vision Optics Sensors Visual Social Computing Computational Photography Imaging Research: Codesign of Optical and Digital Processing Signal Processing Computational Light Transport Displays Machine Learning HCI
  8. 8. Capture Analyze Share Capture Analyze Share ViSoCo
  9. 9. Camera Culture Creating new ways to capture and share visual information MIT Media Lab Ramesh Raskar http://cameraculture.info Facebook.com/cameraculture 1.Light-Field Camera A new camera design exploiting the fundamental dictionary of light-fields for a single-capture capture of light- fields with full-resolution refocusing effects. 2. Color Primaries A new camera design with switchable color filter arrays for optimal color fidelity and picture quality on scene geometry, color and illumination. 3. Flutter-Shutter A camera that codes the exposure time with a binary pseudo-sequence to de- convolve and remove motion blur in textured backgrounds and partial occluders. 4. Compressive Capture We analyze the gamut of visual signals from low-dimensional images to light-fields and propose non-adaptive projections for efficient sparsity exploiting reconstruction. Computational Photography 1. Looking around corners Using short laser pulses and fast detector, we aim to build a device that can look around corners with no imaging device in the line of sight using time resolved transient imaging. 2. Reflectance Recovery We demonstrate a new technique that allows a camera to rapidly acquire reflectance properties of objects 'in the wild' from a single viewpoint, over relatively long distances and without encircling equipment. 3. Trillion Frames per Second Imaging A camera fast enough to capture light pulses moving through objects. We can use such a camera to understand reflectance, absorption and scattering properties of materials. Femtosecond Imaging 3D Displays 1. Tensor Display A family of compressive light field displays comprising all architectures employing a stack of time- multiplexed, light-attenuating layers illuminated by uniform or directional backlighting 2. Layered 3D Tomographic techniques for image synthesis on displays composed of compact volumes of light- attenuating material. Such volumetric attenuators recreate a 4D light field or high-contrast 2D image when illuminated by a uniform backlight. 3. Glasses-free 3D HDTV Light field displays with increased brightness and refresh rate by stacking a pair of modified LCD panels, exploiting rank and constraint of 3D displays 4. BIDI Screen A thin, depth-sensing LCD for 3D interaction using light fields which supports both 2D multi-touch and unencumbered 3D gestures. 5. Living Windows 6D Display A completely passive display that responds to changes in viewpoint and changes in incident light conditions. May 2012
  10. 10. 1. Augmented Light Fields Expands light field representations to describe phase and diffraction effects by using the Wigner Distribution Function displays by analyzing their operations and limitations in phase space 3. Ray–Based Diffraction Model Simplified capture of diffraction model Post-Doctorial Researchers: Doug Lanman, Gordon Wetzstein, Alex Olwal, Christopher Barsi Research Assistants: Matthew Hirsch, Otkrist Gupta, Nikhil Naik, Jason Boggess, Everett Lawson, Aydın Arpa, Kshitij Marwah Visiting Researchers & Students: Di Wu, Daryl Lim 1. Retinal Imaging With simplified optics and cleaver illumination we visualize images of the retina in a standalone device easily operated by the end user. 2. NETRA/CATRA Low-cost cell-phone attachments that measures eye-glass prescription and cataract information from the eye. 3. Cellphone Microscopy A platform for computational microscopy and remote healthcare 4. High-speed Tomography A compact, fast CAT scan machine using no mechanical moving parts or synchronization. 5. Shield Fields 3D reconstruction of objects from a single shot photo using spatial heterodyning. 6. Second Skin Using 3D motion tracking with real- time vibrotactile feedback aids the correct of movement and position errors to improve motor learning. Health & Wellness 1. Bokode Low-cost, passive optical design so that bar codes can be shrunk to fewer than 3mm and read by ordinary cameras several meters away. 2. Specklesense Set of motion-sensing configurations based on laser speckle sensing . The underlying principles allow interactions to be fast, precise, extremely compact, and low cost. 3. Sound Around Soundaround is a multi-viewer interactive audio system, designed to be integrated into multi-view displays presenting localized audio/video channels with no need for glasses or headphones. Human Computer Interaction Visual Social Computing 1. Photocloud A near real-time system for interactively exploring a collectively captured moment without explicit 3D reconstruction. 2. Vision Blocks On-demand, in-browser, customizable, computer-vision application-building platform for the masses. Without any prior programming experience, users can create and share computer vision applications. 3. Lenschat LensChat allows users to share mutual photos with friends or borrow the perspective and abilities of many cameras. Light Propagation Theory and Fourier Optics Visit us online at Cameraculture.info fb.com/cameraculture
  11. 11. Visual Social Computing
  12. 12. Xd X++ X X+Y X X neXt How to come up with new ideas?
  13. 13. Great Research: Strive for Five 1. Before Five teams Be first, often let others do details 2. Beyond Five years What no one is thinking about 3. Within Five layers of ‘Human’ Impact Relevance 4. Beyond Five minutes of description Deep, iterative, participatory 5. Fusing Five+ Expertise Multi-disciplinary, proactive Ramesh Raskar, http://raskar.info
  14. 14. Ramesh Raskar, MIT Media Lab Pick atleast 2 out of 3 Fun Cool Media Coverage Impact Money Social implications Research Novelty Generality Science
  15. 15. What distinguishes ML projects .. – Synthesize not just analyze – Use power of human intelligence • Intelligence Amplification • Human in loop, – Democratize, Power to the People – Be paranoid .. Are we relevant and what is next? Topics for discussion (create your own group) • How to pursue 'ideas in the spirit of the media lab'? What is not in the spirit of ML? • How to make the best of ML resources? • What are the common problems in picking/initiating/pursuing/finishing great projects? • Case studies of successful transitions of efforts into research/demos/products and more • Some procedural topics: juggling classes vs research, Apprenticeship vs independent research, group dynamics, media coverage Ramesh Raskar, http://raskar.info
  16. 16. Be proactive not reactive Generalize today’s concepts Avoid basing all on facebook/twitter/kinect etc or today’s hot tech But we are still slaves to available tech “Let’s do smart things with stupid technology today, rather than wait and do stupid things with smart technology tomorrow” - Bill Buxton. You can ofcourse do even smarter things with smart tech. Be prepared but careful on what you do Be in optimist but be paranoid (vs pessimist + laidback) Defer judgment (don’t dismiss, believe or start instantly on any idea) Overnight success after months of work Have a list of 10-20 problems .. Don’t work on first one you think or that comes your way Talk to a lot of people (you trust) to see if worth purusing as most ideas will be useless anyway Don’t be religious, listen to others I often find people too much in love with a tiny incremental idea if they came up with themselves Try and change what is difficult to some other situation which is easily done but is still important Don’t work on same project for 2+ years Fail fast If u want to win .. Be willing change rules of the game, sometimes the game itself Remember the 4Ps and their SEQUENCE – Projects > Papers > Polished Demo/Prototype > Press – (Note ‘polished demo’ comes AFTER a paper or some external validation) – Don’t chase press before you have a serious project that is peer-reviewed or validated (novelty and impact should be already understood) Ramesh Raskar, http://raskar.info

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