1. CS332 Visual Processing Department of Computer Science Wellesley College Analysis of Motion Recovering observer motion

2. 1-2 Recovering 3D observer motion & layout FOE: focus of expansion

3. 1-3 Application: Automated driving systems DARPA Urban Challenge

4. 1-4 Observer motion problem From image motion, compute:  Observer translation (T x T y T z )  Observer rotation (R x R y R z )  Depth at every location Z(x,y)

5. 1-5 Human perception of heading Human accuracy: 1° - 2° visual arc birds’ eye view Observer heading to the left or right of target on horizon? Warren & colleagues

6. 1-6 Observer just translates toward FOE Directions of velocity vectors intersect at FOE But… simple strategy doesn ’ t work if observer also rotates heading point

7. 1-7 Observer Translation + Rotation Display simulates observer translation Observer rotates their eyes Display simulates translation + rotation Still recover heading with high accuracy

8. 1-8 Observer motion problem, revisited From image motion, compute:  Observer translation (T x T y T z )  Observer rotation (R x R y R z )  Depth at every location Z(x,y) Observer undergoes both translation + rotation

9. 1-9 Equations of observer motion

10. 1-10 Translational component of velocity Where is the FOE? x = y = Example 1: T x = T y = 0T z = 1 Z = 10 everywhere V x = V y = Sketch the velocity field Example 2: T x = T y = 2T z = 1 Z = 10 everywhere V x = V y =

11. 1-11 Longuet-Higgins & Prazdny  Along a depth discontinuity, velocity differences depend only on observer translation  Velocity differences point to the focus of expansion

12. 1-12 Rieger & Lawton ’ s algorithm  At each image location, compute distribution of velocity differences within neighborhood  Find points with strongly oriented distribution, compute dominant direction Appearance of sample distributions:  Compute focus of expansion from intersection of dominant directions