Course Introduction and Philosophy

• Instructor: Ramesh Raskar, MIT Media Lab Camera Culture group
• Course numbers: MAS 131 (undergraduate), MAS 531 (graduate)
• Equipment value: $50,000-$60,000 worth of cameras and imaging equipment
• Core philosophy: Pure digital cameras are "extremely boring" - focus on computational approaches beyond traditional photography

Rolling Shutter Effect Example

• iPhone camera capturing aircraft propeller creates curved blade artifacts
• Demonstrates line-by-line sensor readout vs snapshot assumption
• Rolling shutter reads one line at time due to bandwidth constraints in cell phone cameras
• Opens question: How will photographers exploit future camera artifacts for artistic purposes?

Computational Illumination Techniques

• Shower curtain photography: Using programmable flash to see person behind translucent barrier
• Single photodetector + projector system: Turn on 1 million projector pixels sequentially, record 1 million measurements
• Creates 4D relationship between projector pixels and camera pixels (10^12 measurements)
• Applications: Reading opponent's cards across table using light transport inversion
• Limitation: Requires placing projector in target location

Camera Market Evolution

• 2008-2009: ~1 billion cameras sold annually
• 2001-2002: Zero cameras sold embedded in mobile phones
• Zero to 1 billion cameras in 6 years represents massive market shift
• Camera distribution breakdown:
  • Largest: Mobile phones (pink segment)
  • Optical mice: ~100 million (20x20 or 32x32 pixels, 1000-2000 Hz)
  • Digital/video cameras
  • Gaming applications
  • Security (very small sliver)

3D Imaging Challenges

• Current 3D cameras cost $10,000+, limited quality
• Time-of-flight demonstration: People in green (front), others in back
• Market driven by gaming consoles (PlayStation, Xbox) for gesture interaction
• Technical challenges:
  • Active light compensation for ambient scenes
  • Multi-view geometry stitching
  • Subsurface scattering in materials
  • Specular/dark objects problematic

Multi-Aperture Camera Demo

• 25 separate cameras in single chassis
• Software-based refocusing by shifting/combining images
• Cost: $20,000+ from Viewplus, up to 30-60K for advanced versions
• Demonstrates focus-based depth extraction using baseline between cameras

Biological Vision Systems

• 8 categories of successful biological vision systems
• Scallop eyes: Mirror-based (concave mirror + detector) vs lens-based
• Human vision: Single-chambered with lenses (small subset of possibilities)
• Future cameras could explore other biological architectures

Course Structure and Grading

• Undergraduate (131): 3 assignments, simplified midterm
• Graduate (531): 4 assignments, full midterm
• Grade breakdown:
  • Assignments: 40%
  • Final project: 30%
  • Midterm: 20%
  • Class participation: 10%
• Best project award available
• Last year: 3 projects → SIGGRAPH/ICCV papers, 2 projects → multi-hundred thousand dollar research initiatives

Course Tracks and Prerequisites

• Software-intensive track: GUI-based tools
• Software-hardware track: Programming (OpenCV, MATLAB, C++, etc.)
• Critical skill: Ability to think in 3D
• Helpful but not required: Linear algebra, signal processing, image processing
• Assignment structure: 60-70% accessible to all backgrounds, final 20-30% requires advanced knowledge
• Performance normalized based on student background

Course Focus Areas

• Photography: Higher-dimensional imaging (light fields, thermal, range cameras)
• Active Computer Vision: HCI applications, robotics, tracking, segmentation
• Scientific Imaging: Compressive sensing, wavefront coding, deconvolution, tomography

Three Themes of Computational Photography

• Epsilon Photography: Generalized bracketing (HDR, panorama, focus stacking)
• Coded Photography: Reversible encoding of scene information, feature-revealing cameras
• Essence Photography: High-level scene understanding beyond pixels

Thermal Imaging Applications

• Sports analysis example: Cricket ball impact detection (bat vs pad)
• Current cost: Several thousand dollars
• Goal: Reduce to consumer camera prices ($500 in 5 years)
• Guest: Mathias from Redshift thermal imaging company

Upcoming Conference Opportunity

• 2nd International Conference on Computational Photography
• Location: MIT, last week of March
• Paper deadline: November
• Organized by Raskar, Kutulakos (Toronto), Fergus (Colorado)
• Industry interest: Nokia, Samsung, Canon, HP research groups

Course Logistics

• Classes end December 4th (week before final exam period)
• Friday happy hour continuation at Hotel Charles
• Guest lectures and online discussions
• Class notes assignment for credit students
• Listeners encouraged to participate and contribute expertise