lec19 - Announcements HW 4 due Friday Final Exam Tuesday...

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CSE152, Spr 11 Intro Computer Vision Recognition III Introduction to Computer Vision CSE 152 Lecture 19 CSE152, Spr 11 Intro Computer Vision Announcements • HW 4 due Friday • Final Exam: Tuesday, 6/7 at 8:00-11:00 CSE152, Spr 11 Intro Computer Vision CSE Peer Mentoring Program seeking volunteers • Was your first quarter at UCSD hard? • Would you like to help others through this time? • We are seeking volunteers for a new peer mentoring program – Each mentor will work with a few new majors • just a couple hours per week – Mentors will be advised by CSE graduate students – Mentorship will look great on your resume • Visit this URL to fill out a short form, and we’ll contact you over the summer: http://goo.gl/xLAAj • Questions? Contact Bill Griswold: [email protected] CSE152, Spr 11 Intro Computer Vision Object Recognition: The Problem Given: A database D of “known” objects and an image I: 1. Determine which (if any) objects in D appear in I 2. Determine the pose (rotation and translation) of the object Segmentation (where is it 2D) Recognition (what is it) Pose Est. (where is it 3D) WHAT AND WHERE!!! CSE152, Spr 11 Intro Computer Vision Sketch of a Pattern Recognition Architecture Feature Extraction Classification Image (window) Object Identity Feature Vector CSE152, Spr 11 Intro Computer Vision Example: Face Detection • Scan window over image. • Search over position & scale. • Classify window as either: – Face – Non-face Classifier Window Face Non-face
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The Space of Images • Consider an n-pixel image to be a point in an n- dimensional space, x ! R n . • Each pixel value is a coordinate of x . x 1 x 2 x n x 1 x n x 2 CSE152 Computer Vision I Appearance-based (View-based) Face Space: – A set of face images construct a face space in R n – Appearance-based methods analyze the distributions of individual faces in face space Some questions: 1. How are images of an individual, under all conditions, distributed in this space? 2. How are the images of all individuals distributed in this space? CSE152, Spr 11 Intro Computer Vision Nearest Neighbor Classifier x 1 x 2 x 3 ID = argmin j dist ( R j , I ) CSE152 Computer Vision I An idea: Represent the set of images as a linear subspace What is a linear subspace? Let V be a vector space and let W be a subset of V . Then W is a subspace iff: 1. The zero vector, 0 , is in W . 2. If u and v are elements of W , then any linear combination of u and v is an element of W ; a u + b v ! W 3. If u is an element of W and c is a scalar from K , then the scalar product c u ! W A d -dimensional subspace is spanned by d linearly independent vectors It is spanned by a d-dimensional orthogonal basis. Example: A 2-D linear
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lec19 - Announcements HW 4 due Friday Final Exam Tuesday...

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