Raskar Emtech2010 Mar Final
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Raskar Emtech2010 Mar Final
- 1. Camera Culture Ramesh Raskar Camera Culture MIT Media Lab http://raskar.info http://cameraculture.info Ramesh Raskar Associate Professor Future of Imaging
- 2. Film-like Digital Photography
- 4. Cameras Phones are Everywhere Kush R. Varshney, “ Jagannath Temple ,” Puri, Orissa, India, Dec. 2007.
- 6. Computational Photography Computational Illumination Computational Camera Scene : 8D Ray Modulator Display Generalized Sensor Generalized Optics Processing Ray Bender Ray Sampler Ray Reconstruction Generalized Optics Recreate 4D Lightfield Light Sources Modulators 4D Incident Lighting 4D Light Field
- 7. Can you look around a corner ?
- 9. Convert LCD into a big flat camera ?
- 11. Fernald, Science [Sept 2006] Shadow Refractive Reflective
- 12. Mimicking the Human Eye Lens Detector Pixels Image Slide by Shree Nayar Reproduce for the eye
- 13. Where are the ‘camera’s?
- 14. Where are the ‘camera’s?
- 17. Media Lab Vision Biomechatronics Neuroengineering Smart Fabrics Rethinking Cameras Human 2.0 Multimedia Ubiquitous Computing Social Media Computer Vision Sensor Networks Software Agents Bits Atoms People 1990s Body Brain Technology 2007+ Publishing Broadcast Computer 1980s
- 18. Close Ties With Industry 03/08/10 R E S E A R C H S T R A T E G Y Our 65 corporate sponsors include some of the most creative companies in the world
- 20. Smart Cities What if cars could stack like shopping carts in cities? Ryan Chin and Bill Mitchell
- 21. ADAPTABILTIY Hyper - Adaptability Bio- Mechatronics Music/Mind/ Health People - Sense Sociable Robots Neuro- Media HUMAN ADAPTABILITY Bio- Mechatronics Neuro- Media Sociable Robots People - Sense Music/Mind/ Health
- 22. Camera Culture Ramesh Raskar Ramesh Raskar Associate Professor, MIT Media Lab http://raskar.info New Emerging Technologies Medical Imaging Entertainment User Interfaces Industrial Vision The impact of Next Billion Cameras Movie-making, news reporting Social stability Visual Social Computing Image-based commerce Future of Imaging
- 24. Self Evaluation of Eye
- 26. Self Evaluation of Eye
- 30. What are the problems with ‘real’ photo in conveying information ? Why do we hire artists to draw what can be photographed ?
- 31. Shadows Clutter Many Colors Highlight Shape Edges Mark moving parts Basic colors
- 32. Cartoon Camera Using Depth Edges
- 37. Canny Intensity Edge Detection Our Method Photo Result
- 39. Convert LCD into a big flat camera ? Beyond Multi-touch: 3D Gestures
- 40. Large Virtual Camera for 3D Interactive HCI and Video Conferencing Matthew Hirsch, Henry Holtzman Doug Lanman, Ramesh Raskar Siggraph Asia 2009 BiDi Screen
- 41. Touch + Hover using Thin, Depth Sensing LCD Sensor
- 42. Sensing Depth from Array of Virtual Eyes in LCD
- 43. Photos of tomorrow: computed not recorded http://scalarmotion.wordpress.com/2009/03/15/propeller-image-aliasing/
- 44. Synthesis Low Level Mid Level High Level Hyper realism Raw Angle, spectrum aware Non-visual Data, GPS Metadata Priors Comprehensive 8D reflectance field Computational Photography Digital Epsilon Coded Essence Computational Photography aims to make progress on both axis Camera Array HDR, FoV Focal stack Decomposition problems Depth Spectrum LightFields Human Stereo Vision Transient Imaging Virtual Object Insertion Relighting Augmented Human Experience Material editing from single photo Scene completion from photos Motion Magnification Phototourism Resolution
- 46. Can you ‘see’ around a corner ?
- 47. Femto-Photography: Higher Dimensional Capture FemtoFlash UltraFast Detector Computational Optics Serious Sync
- 48. Application: Rescue and Planning
- 50. Bokode
- 52. Defocus blur of Bokode
- 53. Coding in Angle Mohan, Woo, Smithwick, Hiura, Raskar [Siggraph 2009]
- 56. cell-phone camera close to the Bokode (10,000+ bytes of data)
- 59. Power of the Processor Power of the Network Power of People 1985 1995 2005 2015 Powershifts
- 60. Crowdsourcing http://www.wired.com/wired/archive/14.06/crowds.html Amazon Mechanical Turk: Steve Fossett search ReCAPTCHA=OCR
- 62. Cameras in Developing Countries http://news.bbc.co.uk/2/hi/south_asia/7147796.stm Community news program run by village women
- 65. Socio-Political Goals: B’Tselem From websiteof : Israeli Information Center for Human Rights in the Occupied Territories
- 66. Truth in Images From Hany Farid LA Times March’03
- 67. Vision thru tongue http://www.pbs.org/kcet/wiredscience/story/97-mixed_feelings.html Solutions for the Visually Challenged http://www.seeingwithsound.com/
- 68. Camera Culture Ramesh Raskar How will the next billion cameras change the social culture ? How can we augment the camera to support best ‘image search’ ? How will camera improve trust and social stability ? How will movie-making, news reporting change ? Next model for image-based commerce ? Visual Social Computing
- 70. Camera Culture Ramesh Raskar Ramesh Raskar Associate Professor, MIT Media Lab http://raskar.info New Emerging Technologies Medical Imaging Entertainment User Interfaces Industrial Vision The impact of Next Billion Cameras Movie-making, news reporting Social stability Visual Social Computing Image-based commerce Future of Imaging
- 71. END Part 1
- 72. Start Part 2
- 73. Camera Culture Ramesh Raskar Camera Culture MIT Media Lab http://raskar.info http://cameraculture.info Ramesh Raskar Associate Professor
- 74. After X , what is ne X t How to Invent? Ramesh Raskar, MIT Media Lab
- 75. X d X++ X X+Y X X ne X t Ramesh Raskar, MIT Media Lab
- 80. Example of digital refocusing
- 82. Self Evaluation of Eye
- 86. Power of the Processor Power of the Network Power of People 1985 1995 2005 2015 Powershifts
- 96. X d X++ X X+Y X X ne X t Ramesh Raskar, MIT Media Lab
- 97. End Part 2
- 98. Camera Culture Ramesh Raskar Camera Culture MIT Media Lab http://raskar.info http://cameraculture.info
- 99. Extra Slides
- 100. CREATIVITY Civic Media Next Billion Network Siftables Scratch Hyper - Creativity High- Low Tech CREATIVE ANARCHY Civic Media Next Billion Network Siftables Scratch High- Low Tech
- 101. AWARENESS New Media Medicine Smart Cities Sense-able Societies Hyper- Awareness Human Speechome X-Reality TOTAL AWARENESS Human Speechome Sense-able Societies X-Reality Smart Cities New Media Medicine
- 102. Today a billion plus people enjoy the benefits of a digital lifestyle BUT The deep impact of technology on individuals, society and business lies just ahead. Frank Moss, MIT Media Lab
- 103. Future of the Individual Future of Society Future of Business
- 104. Future of the Individual Future of Society Future of Business
Editor's Notes
- Ramesh Raskar Associate Professor MIT Media Lab http://raskar.info http://cameraculture.info
- Kodak DCS400 in Nikon F3 body in early 90’s Commendable first 1.3MP digital but film cartridge still there! (First one in 1991 but even in 1995 the space for cartridge) Quote from Jack Tumblin Digital photography is like a caged lion that is uncaged in a jungle after years .. The lion stays in place rather than rushing out to explore Billion cameras but they all look like human eye KODAK Professional Digital Camera DCS-100: a camera back and camera winder fitted to an unmodified Nikon F3 camera
- Wishlist by consumers and companies today .. i.e. what is NOT available today but they wish it was So, I am not including Wifi, GPS, face detection etc in the list here. But let us dream beyond this list.
- 4 blocks : light, optics, sensors, processing, (display: light sensitive display) + 5 th element: Network
- Lets dream big .. Can we look around at something beyond the line of sight?
- Can photos become emotive abstract renderings ?
- How to exploit Sharp’s photosensing LCD originally designed for touch sensing and convert into a large area flat camera Since we are adapting LCD technology we can fit a BiDi screen into laptops and mobile devices.
- CPUs and computers don’t mimic the human brain. And robots don’t mimic human activities. Should the hardware for visual computing which is cameras and capture devices, mimic the human eye? Even if we decide to use a successful biological vision system as basis, we have a range of choices. For single chambered to compounds eyes, shadow-based to refractive to reflective optics. So the goal of my group at Media Lab is to explore new designs and develop software algorithms that exploit these designs.
- currently we solve the human visual perception problem by simply reproducing what the eye would see. (even for 3D, we show stereo pair) But this makes it difficult to understand or manipulate for computers. (machine readable rep)
- Platforms = optics, illum + Applications + Social Impact
- So how will the next billion cameras in people pocket change us? Will optically smart sensor help disabled people, portable devices improve social stability and pixel-coordinated activities harness the power of crowdsourcing for image-based commerce?
- (add pic here .. Camera is simplified .. Medical imaging is not)
- Very complex or very rudimentary
- Beautiful theory but strikingly simple implementation .. Combination of simple optics and some intelligent software Based on wavefront manipulation
- Moving towards penny diagnostics Click Diagnostics Hardware app store not just software app store, we have seen this with Wii and Guitarhero
- How to exploit Sharp’s photosensing LCD originally designed for touch sensing and convert into a large area flat camera Since we are adapting LCD technology we can fit a BiDi screen into laptops and mobile devices.
- So here is a preview of our quantitative results. I’ll explain this in more detail later on, but you can see we’re able to accurately distinguish the depth of a set of resolution targets. We show above a portion of portion of views form our virtual cameras, a synthetically refocused image, and the depth map derived from it.
- photos will be computed rather than recorded Comp photo will be there It will change the workflow, just with digital many pipeline have turned upside down and we will even more At the same time with cameras that understand our world better, there will be a lot of new opportunities http://scalarmotion.wordpress.com/2009/03/15/propeller-image-aliasing/
- Pioneered by Nayar and Levoy Synthesis Minimal change of hardware Goals are often opposite (human perception) Use of non-visual data And Network
- = Material index and compute bounces (real vs fake) = Automatic 3D, phototourism, and 3D awareness (look around a corner) = Find relationship (network) between all photos = Understand the world (recognize, categorize, make world smarter bokode)
- If you can look around a corners, firefighters can use such a device for planning rescue of trapped people without actually having to go in the line of fire
- Bokode.com
- = Material index and compute bounces (real vs fake) = Automatic 3D, phototourism, and 3D awareness (look around a corner) = Find relationship (network) between all photos = Understand the world (recognize, categorize, make world smarter bokode)
- Very challenging but a new trend is emerging: in using the power of the people.
- What is the key resource we have in India ..
- The camera phone provides an easy interface to fill in and verify government forms. The paper form is printed with 2D bar-codes which are decoded by camera phone and info is transmitted to a central location.
- Microsoft Photosynth and U-Washington’s Phototourism software takes a large collection of photos of a place or an object, analyzes them for similarities, and then displays the photos in a reconstructed three-dimensional space , showing you how each one relates to the next. New options on Google Maps allows users to post and view populated map with geo-tagged photos provided by Panoramio .
- Israeli Information Center for Human Rights in the Occupied Territories captures photos of events. From their website: “Goal is to Document and educate Israeli public and policymakers about human rights violations in Occupied Territories. Second goal is to combat phenomenon of denial prevalent among Israeli public. We hope to create human rights culture in Israel.”
- So how will the next billion cameras in people pocket change us? Will optically smart sensor help disabled people, portable devices improve social stability and pixel-coordinated activities harness the power of crowdsourcing for image-based commerce? Not outsourcing but image-based crowdsourcing
- So how will the next billion cameras in people pocket change us? Will optically smart sensor help disabled people, portable devices improve social stability and pixel-coordinated activities harness the power of crowdsourcing for image-based commerce?
- Ramesh Raskar Associate Professor MIT Media Lab http://raskar.info http://cameraculture.info
- Six ways of coming up with new ideas based on an idea ‘X’. Ramesh Raskar Associate Professor MIT Media Lab http://raskar.info http://cameraculture.info http://raskar.info http://cameraculture.info
- X up: Airbags for car, for helicopter
- Beautiful theory but strikingly simple implementation .. Combination of simple optics and some intelligent software Based on wavefront manipulation
- Moving towards penny diagnostics Click Diagnostics Hardware app store not just software app store, we have seen this with Wii and Guitarhero
- Shielded by screening pigment. The visual organ provides no spatial information, but by comparing the signal from 2 organs or by moving the body, the worm can navigate towards brighter or darker places. It can also keep certain body orientation. Despite lack of spatial vision, this is an evolutionary forerunner to real eyes.
- http://raskar.info http://cameraculture.media.mit.edu