CAP 5415 Computer Vision General n n n

































- Slides: 33
CAP 5415 Computer Vision
General n n n Instructor: Dr. Alper Yilmaz Email: yilmaz@cs. ucf. edu Office: CSB 250
Course n Office hours n n n Grading n n n Midterms (2) 20% Final 30% Assignments (bi-weekly) %20 Projects (2) %30 Class notes n n Monday 3. 00 pm-4. 30 pm Wednesday 3. 00 pm-4. 30 pm “Fundamentals of computer vision”, Dr. Mubarak Shah available on web page (http: //www. cs. ucf. edu/courses/cap 6411/book. pdf) Text book n “Introductory Techniques for 3 D Computer Vision” Trucco and Verri, Prentice Hall.
Topics We’ll Cover n n n n n Imaging Geometry Camera Modeling and Calibration Filtering and Enhancing Images Region Segmentation Color and Texture Line and Curve Detection Shape Analysis Stereo We may change order Motion and Optical Flow Structure from X
Computer Vision n Image Analysis n n n Single frame Image Understanding Video Analysis n n Multiple frames, temporal information Video Understanding
Generating an Image n 3 D Scene n n Surface reflectance Surface structure (shape) Light source Camera
Perspective Projection 3 D world (X, Y, Z) f Pin hole camera Image plane y Z
Orthographic Projection 3 D world (X, Y, Z) y Image plane Z
Discrete Domain Image n Set of integer values in two dimensions n n Gray level image (1 matrix n n 0: Black 255: White Color image (3 matrices) n n 0 -255 Red, Green, Blue Resolution n Number of rows, number of columns
Video n Sequence of image n n n Frames per second Gray level video Color video
Digitization n Analog camera n n n Analog to Digital converter Frame grabber Digital camera n n Already digitized MPEG or JPEG
Image Formats n n n n TIFF JPEG PGM, PPM PNM BMP MPEG Quick Time…
Computer Vision n Shape From “X” n n Shading (single image) Texture (single image) Stereo (two images) Motion (multiple images)
Stereo
http: //www. vision 3 D. com/stereo. html
Example
Stereo Pair
Stereo Fun candy dinosaur shark
Shape from Shading
Lambertian Surface Model surface normal light source
Sphere Example
Vase Image (1, 0, 1) (-1, 1, 1) (-1, 1)
Object Motion Video Sequence of images
An Image from Hamburg Taxi Sequence
Video Mosaics
Vision Lab. Sequence
Beach Volley Sequence
Sprite
Tracking in Multiple Cameras n n n Find field of view (FOV) lines Detect objects Associate objects
Story Segmentation
Explosion/fire Detection