Required Reading:
• An Invitation to Visual Computing (Lecture Notes)

Suggested Reading:
• The Rise of Mobile Visual Computing Systems (IEEE Pervasive Computing, 2016)

Buzzwords: Affine transformation, transformation matrix, scaling, rotation, identity matrix, translation, camera projection, matrix decomposition, singular value decomposition, unitary matrix, orthogonal vector

Required Reading:
• Fundamentals of Computer Graphics (4e), Chapter 6. We didn't discuss the materials in 6.1.2, 6.1.4, 6.2.1, 6.2.2, 6.4; skip or skim them if you want.

Suggested Reading:
• Read Fundamentals of Computer Graphics (4e), Chapter 5 if you need to refresh basic linear algebra. Study 5.4 carefully if you haven't seen that material before.

Buzzwords: Inner product, projection, Fourier Series, Fourier Transform, Discrete Fourier Transform, spectrum, low-pass filter, high-pass filter

Required Reading:
• Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control, Chapter 2.1, 2.2. Focus on getting the idea; skip the math proofs if you want; pay attention to how they see Fourier Transform from a vector-space perspective. Skim 2.6 if you want.

Suggested Reading:
• Play with the sample programs I used in the class today (reconstruct.py, filter.py, visterms.py). Run them and understand how they work.

Buzzwords: Nyquist-Shannon sampling theorem, signal sampling, signal reconstruction, convolution, convolution theorem, compressed sensing, downsampling and upsampling, resampling

Required Reading:
• Fundamentals of Computer Graphics (4e), Chapter 9.1, 9.2, and 9.6. Skim other chapters in 9.

Suggested Reading:
• Physically-Based Rendering (4ed), Chapter 8.1.
• Image Filtering Tutorial. Nice illustrations of filtering/convolutions. Has more filter types than what we discussed in the class.

Buzzwords: Eyes, lens, cornea, spectral transmittance, retina, RGCs, bipolar cells, horizontal cells, amacrine cells, fovea, photoreceptors, cones, rods, blind spot, light spectrum, spectral power distribution, photopic vision, scotopic vision, Weber contrast, Michelson contrast, receptive field, adaptation, center-surround, excitatory, inhibitory, tuning curves, LGN, visual cortex, simple cells, complex cells, orientation selectivity, visual streams, parallel pathways, ventral pathway, dorsal pathway

Buzzwords: Principle of Univariance, Beer-Lambert law, transmittance, absorptance, absorbance, spectral sensitivity, cone fundamentals, macular pigments, phototransduction, pigments, isomerization, opsin, retinal, cG, cG-gated ion channels, phototransduction deactivation, negative feedback, undershoot, pigment regeneration, retinal pigment epithelium, dark noise

Buzzwords: cone fundamentals, equal-energy, equal-quantal, invisible light, total cone responses, LMS color space, gamut, metamerism, metamer, color matching experiment, color matching function, spectral locus, trichromatic theory of color, opponent processes, hue cancellation, luminous efficiency function, spectrally-opponent cells

Required Reading:
• Interactive tutorial, Building a Color Space From Cone Fundamentals.

Suggested Reading:
• How the CIE 1931 RGB Color Matching Functions Were Developed from the Initial Color Matching Experiments. An article I wrote that explains how exactly the color matching functions are derived from the color matching experiments.
• Chapter 2A, Billmeyer and Saltzman's Principles of Color Technology.
• Color opponency: tutorial (by Steven K. Shevell1 and Paul R. Martin; J Opt Soc Am A Opt Image Sci Vis. 2017.)

Buzzwords: Colorimetry, color cube, gamut, quantization, chromaticity, chromaticity plot, chromaticity gamut, XYZ color space, reference white, black-body radiation, Planckian locus, color temperature, correlated color temperature, sRGB, additive color model, subtractive color model, perceptual color space, HSV, HSL, HSB, hue, saturation, value, lightness, brightness, CMYK, gamma, MacAdam ellipses

Required Reading:
• Interactive tutorial, Chromaticity, Gamut, and the Scary World of Imaginary Colors.
• Interactive tutorial, Building a Color Cube.

Suggested Reading:
• Interactive tutorial, CIE 1931 XYZ Color Space.
• Chapter 4A-4D, Billmeyer and Saltzman's Principles of Color Technology. Study carefully Figure 4.23, which is great. Skip materials that I didn't cover in the lecture if you want.

Suggested Reading:
• Interactive tutorial exploring color blindness.

Buzzwords: Pinhole camera, motion blur, convex lens, concave lens, Snell's law, refraction index, gravitational lens, waveguide, thin lens approximation, paraxial approximation, gaussian lens equation, circle of confusion, depth of field, F-number, magnification factor, field-of-view, think lens, optical aberration, chromatic aberration, monochromatic aberration, spherical aberration, motion from blur, depth from blur

Required Reading:
• Chapter 4.2 -- 4.5, Virtual Reality. Talks about cameras, lenses, and optical aberrations at a high level; a pleasant read.

Suggested Reading:
• Archimedes and the Burning Mirror.
• Chapter 5, Optics (5e). Geometrical optics very well explained. Even studying the illustrations alone can get you pretty far.

Buzzwords: IR filter, UV filter, microlens, photoelectric effect, photodiodes, quantum efficiency, light-matter interaction, energy-harvesting camera, pixel well, full-well capacity, saturation, dynamic range, high dynamic range, NIR photography, thermographic camera, IR camera, depth sensing, fill factor, charge-to-voltage conversion, voltage gain, CCD sensor, CMOS sensor, rolling shutter, global shutter, analog-to-digital conversion, ADC, resolution

Required Reading:
• Chapter 2 of Image Processing for Embedded Devices From CFA Data to Image Video Coding. A good overview of camera optics and sensor in general. No math.

Suggested Reading:
• Digital Camera System on a Chip. Read an overview of modern CMOS camera sensors from the person who invented it. A slightly more technical version is here.
• Evolving Image Sensor Architecture through Stacking Devices. Good overview of recent advancements of 3D-stacked image sensors.
• Chapter 3 of Image Sensors and Signal Processing for Digital Still Cameras. It has an in-depth discussion of the various aspects of camera sensors. What's relevant for today's lecture is Chapter 3.1 and 3.2. You can safely skip the math there, but going through it gives you a nice technical understanding of the topic.

Buzzwords: noise, temporal noise, fixed pattern noise, photon shot noise, Poisson distribution, dark current noise, read noise, reset noise, hot pixels, bias/offset voltage, noise amplification, signal to noise ratio, signal gain, ISO, ADC gain, ADC noise, ADC quantization error, correlated double sampling, recover noise-free images, dark-frame subtraction, bias frame, dark frame, flat-field correction, dynamic range, stop, dB, three chip sensor, foveon sensor, bayer pattern, spectral sensitivity function, SSF

Required Reading:
• Noise, Dynamic Range and Bit Depth in Digital SLRs. Read just that first page; an information treatment of different sources of noise.

Suggested Reading:
• ARVR Sensing. Has good slides on image sensor hardware; includes some discussions on Digital Pixel Sensor (DPS), Correlated Double Sampling (CDS), and Time-to-Saturation for high dynamic range imaging.
• Noise and modelling SNR. A great technical discussion on noise.
• CCD Noise Sources and Signal-to-Noise Ratio. Another narrative of sensor noise. Talks about CCD, but the general idea is the same.

Buzzwords: image signal processing, ISP, denoising, filtering, Gaussian filter, low-pass filter, bilateral filter, demosaic, color correction, regression, ColorChecker

Required Reading:
• A Software Platform for Manipulating the Camera Imaging Pipeline (ECCV 2016). It's an open-source ISP pipeline implementation. Our discussion doesn't exactly follow and we will leave a few stages (e.g., tone mapping, white balancing) to later lectures.
• Exploring camera color correction. An interactive tutorial that we developed that walks you through camera color correction.

Suggested Reading:
• Andrew Rowlands' Color conversion matrices in digital cameras: a tutorial is the definitive to camera color correction; give it a read if you are serious about it, which also talks about the connection between color correction and white balance.
• These three articles in a series (1, 2, 3) has a good explanation of color correction too.

Buzzwords: HDR imaging, tone mapping, graduated neutral density filter, GND, multiple exposures, radiance map, linear tone mapping, global tone mapping, local tone mapping, contrast, local contrast, HDR look

Required Reading:
• Tones and Contrast and Tone Curve in Photoshop. They talk about the notion of tone and contrast as well as how changing image tones on a standard DR image changes the visual effects. An interesting thing to note is that tone mapping in SDR images usually uses an S-shape curve that increases the contrast in midtones and compress contrasts in highlights and shadows, whereas tone mapping curves for HDR images tend to be inverse-S shape to bring out details in highlights and shadows.

Suggested Reading:
• Burst photography for high dynamic range and low-light imaging on mobile cameras (SIGGRAPH Asia 2016). The HDR+ pipeline in Google Pixel and Pixel 2.
• Spatially Nonuniform Scaling Functions for High Contrast Images (SIGGRAPH Asia 2016). Early work on exploiting local contrast in tone mapping.
• Recovering High Dynamic Range Radiance Maps from Photographs (SIGGRAPH 1997).

Buzzwords: Feedback-driven optimization, color constancy, chromatic adaptation, neutral point, white point, illuminant, von Kries adaptation model, auto white balancing, AWB, active AF, passive AF, phase detection, contrast detection, PDAF, CDAF, cross-correlation, autofocus point, dual pixel AF, time-of-flight, depth from stereo, structured light, metering

Required Reading:
• Play with the Canon exposure control simulator.
• Chapter 19.3 and 19.4, Fundamentals of Computer Graphics (4e). It provides a gentle introduction to chromatic adaptation and color appearance model.

Suggested Reading:
• Principles and Practices of Chromatic Adaptation. The theory behind basic chromatic adaptation models and their applications in color imaging.
• Synthetic Depth-of-Field with a Single-Camera Mobile Phone (SIGGRAPH Asia 2018).

Buzzwords: Encoder, decoder, codec, lossless, lossy, luma, chroma, chroma subsampling, Y'CbCr, JPEG, DCT, basis function, quantization matrix, entropy encoding, run-length encoding, RLE, Motion-JPEG, M-JPEG, MPEG, H.262, H.264, H.265, AVC, HEVC, container former, .mp4, intra-frame prediction, inter-frame prediction, motion estimation, motion compensated interpolation, three step search, residual, macroblock, motion vector, reference frame, I-frame, P-frame, B-frame, GoP, sub-pixel motion, transcoding

Required Reading:
• Chapter 16, Digital Video and HD : Algorithms and Interfaces. An high-level introduction to video compression, not tied to a particular standard.
• Read the example on page 496-499 in Chapter 45, Digital Video and HD : Algorithms and Interfaces. A JPEG compression walk-through using a different example from what I used in the lecture.

Suggested Reading:
• Chapter 3, The H.264 Advanced Video Compression Standard. A different, but very good, narrative of (H.264) video encoding.
• vbench: Benchmarking Video Transcoding in the Cloud (ASPLOS 2018). Profiling the video transcoding system in Google.
• Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision (ISCA 2018). How motion (naturally generated by cameras) can be used to help computer vision tasks.

Buzzwords: Panorama, field of view, FOV, telephoto lens, perspective projection, ghosting, cylindrical projection, spherical projection, distortion, equi-rectangular projection, cubemap projection, spherical projection, stereo 360, omni-direction stereo, light field, extended depth of field, plenoptic camera, NeRF, photogrammetry, structure from motion, bundle adjustment, ego-motion estimation

Suggested Reading:
• A high-level overview of Facebook Surround 360 algorithm pipeline.
• Bringing pixels front and center in VR video. This Google post talks about the issues with equirectangular projection and introduces the EAC projection.
• NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. Use neural networks to estimate light field.

Buzzwords: Photo-realism, computer-generated imagery, parametric surface, parametric curve, polygon mesh, triangle mesh, point cloud, point set, normal, polygon triangulation, bezier curve, bezier surface, basis functions, Bernstein polynomials, LiDAR, point set triangulation, Delaunay triangulation

Required Reading:
• Read the Scratchapixel articles on Bezier curve and Bezier surface. Feel free to ignore materials that we didn't discuss in the lecture (e.g., joining Bezier curves).
• Chapter 12.1 up till 12.1.1, Fundamentals of Computer Graphics (4e).

Suggested Reading:
• The rest of Chapter 12.1, Fundamentals of Computer Graphics (4e).
• Read the Scratchapixel articles on Introduction to Polygon Meshes.

Buzzwords: rasterization, ray tracing, image-centric, object-centric, visibility, shading, local frame, world frame, camera space, raster space, perspective projection, orthographic projection, environmental camera, near-clipping plane, far-clipping plane, barycentric coordinates, depth-buffer, z-buffer, supersampling, GPU, shader, SIMD

Required Reading:
• Read the first four chapters on this Scratchapixel lession on Rasterization: a Practical Implementation.
• Both this Scratchapixel article and Chapter 7.2 and 7.3 of Fundamentals of Computer Graphics (4e) talk about how to calculate the perspective transformation matrix. They use different conventions but the principle is the same. Go over them to reinforce your understanding. Pay attention to details.

Suggested Reading:
• Chapter 8.6Principles of Digital Image Synthesis. A good discussion of supersampling.
• Chapter 2.7, Fundamentals of Computer Graphics (4e). It provides a pretty detailed discussion of barycentric coordinates for triangles.
• Chapter 4.2, Fundamentals of Computer Graphics (4e). Gives some intuitions behind different projections.
• GPU Computing (Proceedings of the IEEE, 2008). Not the most recent article, but still provides a good overview of the transition from GPU to GPGPU.

Buzzwords: ray-triangle intersection, acceleration structures, space partition, object partition, uniform grid, octree, k-d tree, binary space partitining tree, BSP, bounding volume hierarchy, BVH, recursive ray tracing, whitted-style ray tracing

Required Reading:
• An Overview of the Ray-Tracing Rendering Technique. A brief overview of Whitted's (recursive) ray tracing algorithm. We haven't talked about shading yet, but skim through it; you will get a nice idea of it.
• A Ray-Tracing Pioneer Explains How He Stumbled into Global Illumination. Turner Whitted's retrospective views of how the recursive idea came along and how it was positioned from today's perspective.

Suggested Reading:
• Introduction to Ray Tracing: a Simple Method for Creating 3D Images.
• Chapter 4.3, Physically Based Rendering. A detailed implementation of BVH.

Buzzwords: Phong model, global illumination, ambient shading, rendering equation, bidirectional reflectance distribution function, BRDF, Monte Carlo integration, Monte Carlo estimator, variance, bias, specular lobe, caustic, bidirectional subsurface scattering function, BSSDF, texture mapping, texel, UV unwrapping, UV map, UV island, texture sampling, texture filtering

Required Reading:
• Monte-Carlo integration (from Scratchapixel).
• Introduction to global illumination and path tracing (from Scratchapixel; with code).

Suggested Reading:
• Chapter 11.4 of Fundamentals of Computer Graphics (4e) gives an overview of the applications of texture mapping. Read other sections in the same chapter if you care about the math behind texture mapping.
• Chapter 14.3 of Fundamentals of Computer Graphics (4e) gives a slightly formal treatment of Monte-Carlo integration. Chapter 14.1 and 14.2 review some basic concepts. Chapter 14.4 concerns with random sampling (which is tricker than you think).
• Deriving Lambertian BRDF from first principles. After this lecture you should be able to understand the BRDF derivation in this article.

Buzzwords: Herculaneum Papyri, Archimedes Palimpsest, Hipparchus's Star Catalogue, Scheimpflug imaging, pentimento, The Old Guitarist, The Martellus Map, The Hunt-Lenox Globe, multispectral imaging, structure from motion

Suggested Reading:
• How AI is expanding art history
• Talk on The Archimedes Palimpsest
• Talk on Reading the Herculaneum Papyri: Yesterday, Today, and Tomorrow

Buzzwords: Eye piece, eye relief, virtual display, motion to photon latency, motion tracking, DoF, IMU, gyroscope, accelerometer, inside-out/outside-in tracking, teleportation, stereopsis, vergence-accommodation conflict, light field display, gaze tracking, foveated rendering, ventral metarism, foveated ray tracing, lens distortion, optical see-through, video see-through, waveguide

Required Reading:
• Head-mounted Displays and Lenses.
• Accommodation and Vergence in Head-mounted Displays.

Suggest Reading:
• Fundamentals of 3D imaging and displays: a tutorial on integral imaging, light-field, and plenoptic systems (Advances in Optics and Photonics, 2018).