CAP 5415 Computer Vision

CAP 5415 Computer Vision

General

Instructor: Dr. Alper Yilmaz Email: yilmaz@cs.ucf.edu Office: CSB 250

Course Office hours

Monday 3.00pm-4.30pm Wednesday 3.00pm-4.30pm

Grading Midterms (2) 20% Final 30% Assignments (bi-weekly) %20 Projects (2) %30

Class notes “Fundamentals of computer vision”, Dr. Mubarak Shah

available on web page (http://www.cs.ucf.edu/courses/cap6411/book.pdf)

Text book “Introductory Techniques for 3D Computer Vision” Trucco

and Verri, Prentice Hall.

Topics We’ll Cover Imaging Geometry Camera Modeling and Calibration Filtering and Enhancing Images Region Segmentation Color and Texture Line and Curve Detection Shape Analysis Stereo Motion and Optical Flow Structure from X

We may change order

Computer Vision

Image Analysis Single frame Image Understanding

Video Analysis Multiple frames, temporal information Video Understanding

Generating an Image

3D Scene Surface reflectance Surface structure (shape)

Light source Camera

Perspective Projection

Image

pla

ne

3D world

Pin

hole

ca

mera

Z

f

(X,Y,Z)

y

Z

Yfy

Z

Xfx

Orthographic Projection

Image

pla

ne

3D world

Z

(X,Y,Z)y

Yy

Xx

Discrete Domain Image Set of integer values in two

dimensions 0-255

Gray level image (1 matrix 0: Black 255: White

Color image (3 matrices) Red, Green, Blue

Resolution Number of rows, number of columns

Video

Sequence of image Frames per second Gray level video Color video

Digitization

Analog camera Analog to Digital converter Frame grabber

Digital camera Already digitized MPEG or JPEG

Image Formats

TIFF JPEG PGM, PPM PNM BMP MPEG Quick Time…

Computer Vision

Shape From “X” Shading (single image) Texture (single image) Stereo (two images) Motion (multiple images)

Stereo

http://www.vision3D.com/stereo.html

Example

Stereo Pair

Stereo Fun

candy dinosaur shark

Shape from Shading

Lambertian Surface Model

lightsource

surfacenormal

),,).(,,(.),( zyxzyx lllnnnLNyxf

),,)).(1,,(1

1(.),(

22 zyx lllqpqp

LNyxf

Sphere Example

),,(1

),,(

222

zyxR

nnn

z

y

y

zq

z

x

x

zp

yxRz

zyx

Vase Image

(1, 0, 1) (-1, 1, 1) (-1,-1, 1)

Object Motion

VideoSequence of images

An Image from Hamburg Taxi Sequence

Video Mosaics

Vision Lab. Sequence

Beach Volley Sequence

Sprite

Tracking in Multiple Cameras

Find field of view (FOV) lines Detect objects Associate objects

Story Segmentation

Explosion/fire Detection