1. CS248 Midterm Review Szymon Rusinkiewicz

2. CS248 Midterm Monday, November 1, 7-9 pm Gates B01 and B03 Designed to be 1-hour exam Mostly “short answer” questions Covers through Thursday’s lecture

3. Raster Displays, Resolution, Perception CRTs – physical vs. addressable resolution – 3 phosphors for “red”, “green”, and “blue” – Traditional (triads, shadow mask) vs. Trinitron (stripes, aperture grille) Human spatial frequency sensitivity – General trend: lower sensitivity at higher frequencies – Sensitivity highest in fovea – Phase sensitivity (Vernier acuity)

4. Raster Displays, Resolution, Perception Human temporal frequency sensitivity – Flicker sensitivity – how often must we redraw a CRT to avoid flicker? (50-70 Hz, depending on brightness and contrast) – Perceived motion – update rate – how often must we change the picture so it looks like it is moving? (12 Hz = cartoons, 24 Hz = film, 60 Hz interlaced = video) – Lag time – virtual reality and head- mounted displays – how often must we update to avoid motion sickness (up to 100 Hz)

5. Raster Displays, Resolution, Perception Human intensity sensitivity – How many bits per pixel do we need? (line drawings = 3 bits, full-color pictures = 5-7 or more) – Response to intensity is nonlinear – Power laws, gamma – Gamma in cameras, CRTs; gamma correction Dithering – Trade off spatial resolution for intensity res. – Moves low-frequency error to high freq.

6. Raster Displays, Resolution, Perception Sample questions: 1. A scene is photographed with a TV camera with gamma=0.5 and displayed on a CRT with gamma=2.4. If we want system gamma to be 1.0, we should do gamma correction with what exponent? 2. You are doing clustered-dot dithering on an image for output on a 300 dpi laser printer. If you need at least 75 dpi “effective” resolution, how many shades of gray can you output?

7. Color Perception of color – Three cones sensitive to “red”, “green”, and “blue” – Overlapping response curves Color spaces – , ,  space vs. R, G, B space vs. X, Y, Z space, 3x3 matrices to convert between them – Gamut, chromaticity diagrams

8. Color Combining colors – Additive vs. subtractive mixing – Primaries Intuitive colorspaces – Single and double cones, hexcones – HSL, HSV – When are these useful? When is RGB preferable?

9. Color Sample questions: 1. What are the ideal spectra for the primaries used in additive mixing? Why? 2. The point (255, 127, 127) in RGB space is nearest to what point in single-hexcone HSV space? 3. You are scuba diving at the bottom of the lake, and are looking at the sun through water. Assuming the water scatters blue light, does the sun appear more bluish?

10. Sampling and Antialiasing The sampling and reconstruction pipeline: – Prefiltering – Sampling – Resampling – Reconstruction Fourier transform, aliasing in the frequency domain Filtering and convolution

11. Sampling and Antialiasing Prefiltering vs. postfiltering Desirable filters for antialiasing Supersampling – Regular vs. stochastic Unweighted/weighted area sampling – Why is this an approximation?

12. Sampling and Antialiasing Sample questions: 1. Which of the following would affect your choice of a reconstruction filter? a.Pixel shape b.Choice of prefilter c.Actual size of the display 2. What is the result of convolving a 1-D box filter with itself?

13. Digital Compositing The compositing approximation – Conditions for validity (in theory and in practice) Deriving alpha mattes – Blue screen (or green screen) – Chroma key – Computing during rendering Compositing algebra

14. Digital Compositing Sample question: You are doing the special effects for a movie, and need to composite a computer generated object over a live background. Why should you use an 8-bit alpha matte rather than a binary (1-bit) matte, even if the computer-generated object is fully opaque?

15. Rasterization Rasterization of lines – Definition of “one-pixel-thick” line – which points get rasterized? – DDA algorithm – use coherency to reduce work done at each pixel Rasterization of polygons – General case – AET – Also uses a DDA to maintain endpoints on each scanline – Meshing rules

16. Rasterization Sample question: – If you rasterized this line, which pixels would get turned on?

17. Transformations Homogeneous coordinates – let us represent translation via a matrix multiplication Matrices for rotation, translation, scale, shear in 2D, 3D Composing (concatenating) transformations – multiply matrices in reverse order Classes of transformations

18. Transformations Sample question: Which of the following are commutative? a. Rotation and scale b. Rotation and translation c. Translation and scale