Chapter 24: Perception

1. Chapter 24: Perception April 20, 2004

2. 24.1 Introduction • Emphasis on vision • Feature extraction approach • Model-based approach • S stimulus • W world • f, defined by physics and optics • S = f(W) computer graphics • W = f-1(S) computer vision

3. 24.2 Image Formation • Pinhole Camera (image without a lense) • Figure 24.1 • point P in scene (X, Y, Z) • point P’ in image plane (x, y, z) • f: distance from pinhole to image plane • -x / f = X / Z (similar triangles) • - y / f = Y / Z (similar triangles)

4. Lens Systems • A lens enables more light to enter • The pinhole camera equations are still accurate • Figure 24.2

5. Photometry: Study of Light • Figure 24.3 • Specular reflection: light is reflected from the outer surface of the object • Diffuse reflection: light is absorbed by the object and then re-emitted

6. Color • The retina has three types of cones with receptivity peaks at 650 nm, 530 nm and 430 nm • Colors can be reproduced by using linear combinations of red (700 nm), green (546 nm) and blue (436 nm)

7. 24.3 Early Image Processing Operations • Local operations • Lack of Knowledge • Smoothing: predicting the value of a pixel, given the surrounding pixels • A weighted average can be calculated using a Gaussian filter (cancels Gaussian noise)

8. Edge Detection • Edges occur where there is a significant change in image brightness • Figure 24.4, kinds of edges • Figure 24.5, edges from a photograph • Figure 24.6, calculating edges • Canny edge detection

9. Image Segmentation • Can look at low level knowledge such as brightness, color, or texture • Can also factor in high-level knowledge.