-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathindex.html
195 lines (166 loc) · 7.56 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<link rel="icon" type="image/png" href="data/seal_icon.png">
<title>Advanced Computer Vision</title>
<meta http-equiv="content-type" content="text/html; charset=utf-8" />
<link href="data/default.css" rel="stylesheet" type="text/css" />
<meta property='og:title' content='Advanced Computer Vision' />
<meta property='og:url' content='https://16820AdvancedCV.github.io/' />
<meta property='og:image' content='https://16820AdvancedCV.github.io/data/teaserim.png' />
<meta property="og:type" content="website" />
</head>
<body>
<div id="header">
<div id="logo">
<h1 class="logo-header">
<center>
16-820: Advanced Computer Vision
</center>
</h1>
<h2 class="logo-header">
<center>
Fall 2024
</center>
</h2><br>
<h2 class="logo-header">
<table border="0" align="center">
<td colspan="6" align="center"><span class="menubar">
[ <a href="index.html">Course Page</a> |
<a href="https://canvas.cmu.edu/courses/43480/pages/schedule">Schedule</a> |
<a href="pages/assignments.html">Assignments</a> |
<a href="https://piazza.com/cmu/fall2024/16820a">Piazza </a> |
<a href="https://canvas.cmu.edu/courses/43480/">Canvas</a> |
<a
href="https://docs.google.com/spreadsheets/d/1KqeygOFwX2vjksJBmAmTD724di-kU3ZYyTUkxr7LNq4/edit?usp=sharing">Office
Hours</a> |
<a href="https://drive.google.com/drive/folders/1-H1A-N2XPK5dDSpdYiiolOZusbm73D7W?usp=sharing">Lecture Slides</a>
]
</span></td>
</table>
</h2>
<h2 class="logo-header">
<center>
<span style="font-size:92%;color:#777;font-weight:normal">Monday and Wednesday, 12:30PM-1:50PM, DH [Doherty Hall] 1212</span><br />
</center>
</h2><br>
</div>
<div id="splash">
<center><img src="data/16820-teaser.png" alt="" width="1000" /></center>
</div>
<div id="content">
<h2>Course Description</h2>
<ul>
<!-- TODO update course description -->
<p>
This course introduces the fundamental techniques used in computer vision, which is the analysis of patterns
in
visual images to understand the objects and scenes that generated them. Topics covered include image formation
and representation, camera geometry, and calibration, computational imaging, multi-view geometry, stereo, 3D
reconstruction from images, motion analysis, physics-based vision, image segmentation and object recognition.
Homeworks involve Python programming exercises.
<br>
This course is modeled off of 16-720, but moving at a bit faster pace. We will also have a number of guest
lectures on cutting-edge research in CV.
</br>
</p>
</ul>
<h2>Educational Outcomes</h2>
<ul>
<li>Implement the Hough Transform to detect lines in an image</li>
<li>Detect Harris Corners and implement the RANSAC algorithm to find the homography between two images</li>
<li>Perform object recognition using a convolutional neural network</li>
<li>Perform 3D reconstruction and stereo rectification to implement stereo block matching using two images</li>
<li>Implement a gradient descent based image alignment algorithm to track objects in a video</li>
<li>3D segmentation</li>
<li>Students will learn how to use Python and PyTorch through the programming assignments</li>
</ul>
<h2>Prerequisites</h2>
<p>
<ul>
<li>Linear Algebra, Multivariate Calculus, Probability theory, Programming.</li>
<li>Python programming experience and previous exposure to image processing
are desirable, but not required.<br>
However, your ability to code in Python will be a crucial factor in your
success.
<br>
If you are not familiar with Python, you will need to put in extra effort at the
beginning to learning it quickly.
</li>
</ul>
</p>
<h2>Recommended Books</h2>
<p>
<ul>
<li>Computer Vision: Algorithms and Applications, by Richard Szeliski (<a href="https://szeliski.org/Book/">available online for free</a>)</li>
<li>Multiple View Geometry in Computer Vision, by Richard Hartley and Andrew Zisserman</li>
<li>Computer Vision: A Modern Approach, by David Forsyth and Jean Ponce</li>
<li>Digital Image Processing, by Rafael Gonzalez and Richard Woods</li>
</ul>
</p>
<h2>Grading</h2>
<p>Grade based on 6 homeworks (with considerable Python implementation)
<ul>
<li> HW 1-5 are worth 18% each</li>
<li> HW 6 (last homework) is worth 10% (it’s a bit smaller). </li>
</ul>
Extra credit (worth up to 3% of your final grade):
<ul>
<li> Class participation (Piazza / lecture) </li>
<li> Organizing study groups </li>
</ul>
</p>
<h2>Course Staff</h2>
<p>Please use the course <a href="https://piazza.com/cmu/fall2024/16820a">Piazza page</a> for all communication
with course staff </p>
<h3> Course Instructor </h3>
<div class="instructor">
<a href="https://www.cs.cmu.edu/~motoole2">
<div class="instructorphoto"><img src="./data/motoole.jpg"></div>
<div>Matthew O'Toole</div>
</a>
</div>
</br>
<br>
<h3> Teaching Assistants </h3>
<div class="instructor">
<a href="https://nik-v9.github.io/">
<div class="instructorphoto"><img src="./data/nikhil.jpg"></div>
<div>Nikhil Keetha</div>
</a>
<div>OH: <a
href="https://docs.google.com/spreadsheets/d/1KqeygOFwX2vjksJBmAmTD724di-kU3ZYyTUkxr7LNq4/edit?usp=sharing">(refer
google sheet)</a></div>
</div>
<div class="instructor">
<a href="https://ayushjain1144.github.io/">
<div class="instructorphoto"><img src="./data/ayush.jpg"></div>
<div>Ayush Jain</div>
</a>
<div>OH: <a
href="https://docs.google.com/spreadsheets/d/1KqeygOFwX2vjksJBmAmTD724di-kU3ZYyTUkxr7LNq4/edit?usp=sharing">(refer
google sheet)</a></div>
</div>
<div class="instructor">
<a href="https://www.ri.cmu.edu/ri-people/yuyao-shi/">
<div class="instructorphoto"><img src="./data/yuyao.png"></div>
<div>Yuyao Shi</div>
</a>
<div>OH: <a
href="https://docs.google.com/spreadsheets/d/1KqeygOFwX2vjksJBmAmTD724di-kU3ZYyTUkxr7LNq4/edit?usp=sharing">(refer
google sheet)</a></div>
</div>
<br></br></br>
<!-- <h2>Related Courses</h2>
<br>
If you found this course useful, you may also be interested in the following related courses/tutorials: <br><br>
<a href="https://courses.engr.illinois.edu/cs598dwh/fa2021/"> 3D Vision (UIUC) <br>
<a href="https://learning3d.github.io/"> Learning for 3D Vision (CMU)</a> <br>
<a href="https://www-users.cse.umn.edu/~hspark/CSci5980/csci5980_3dvision.html"> Multiview 3D Geometry in
Computer Vision (UMN) <br>
<a href="https://github.com/mint-lab/3dv_tutorial"> An Invitation to 3D Vision: A Tutorial for Everyone <br>
<br></br></br>
<div style="clear: both;"> </div> -->
</div>
</body>
</html>