Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
Review for
Problem Set 1
CS 231a Winter 201516
Sumant Sharma
Webmaster & SCPD CA
Ph.D. Student, Space Rendezvous Laboratory
Some slides in the presentation are courtesy of
Saumitro Dasgupta (CS 231a CA Winter 201415)
Todays Agenda
Camera Model
Rotation
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
Speech and Language Processing. Daniel Jurafsky & James H. Martin.
rights reserved. Draft of November 7, 2016.
c 2016.
Copyright
All
CHAPTER
16
Semantics with Dense Vectors
In the previous chapter we saw how to represent a word as a sparse vector with
di
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
CS231A Midterm
Review
Friday 5/6/2016
Outline
General Logistics
Camera Models
Nonperspective cameras
Calibration
Single View Metrology
Epipolar Geometry
Structure from Motion
Active Stereo and Volumetric Stereo
Fitting and Matching
RANSAC
Hough Transfo
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
CS 231A Computer Vision, Spring 2016
Problem Set 1
Due Date: April 15th 2016 11:59 pm
1
Projective Geometry Problems [10 points]
In this question, we will examine properties of projective transformations. We define a camera
coordinate system, which is onl
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
CS 231A Computer Vision, Spring 2016
Problem Set 4
Due Date: May 20th 2016 11:59 pm
1
Viewpoint Estimation With Bag of Words
In the previous problem set, we explored object detection with histogram of oriented gradients
and support vector machines. Often,
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
CS 231A Computer Vision (Spring 2016)
Problem Set 3
Due: May 4th, 2016 (11:59pm)
1
Space Carving (25 points)
Dense 3D reconstruction is a difficult problem, as tackling it from the Structure from Motion
framework (as seen in the previous problem set) requ
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
PS2 Review
CS231A
Computer Vision: From 3D Reconstruction to Recognition
Spring 2016
1
Outline
Q2: Estimating Fundamental Matrix
Q3: Affine Structure From Motion
Q4: Projective Triangulation in Structure From Motion
2
Least Squares Eight Point Algorithm
I
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2014
CS 231A Computer Vision (Winter 2016)
Problem Set 2
April 25th 2016 11:59pm
1
Fundamental Matrix (20 points)
In this question, you will explore some properties of fundamental matrix and derive a minimal
parameterization for it.
a Show that two 3 4 camera
Convolutional Neural Networks for Visual Recognition
CS 231N

Winter 2015
Administrative
 Poster Session on Wednesday, worth 3% of final grade,
+2% for top few posters. There will be food
 CS224D (Deep Learning for NLP) was announced for next
quarter taught by Richard Socher, natural followup for
more DL.
FeiFei Li & Andrej