Differences

This shows you the differences between two versions of the page.

--- syllabus [2018/09/04 22:00] – jelder
+++ syllabus [2018/11/07 18:01] (current) – jelder
@@ Line 46: / Line 46: @@
   * [[https://karaimer.github.io/|Hakki Karaimer]]
     * Office: LAS 2052
-    * Office hours: F 11:00AM - 12:00PM
+    * Office hours: Changed as of Nov 7 to Th 11:00AM - 12:00PM
     * Email: hakkicankaraimer@gmail.com
 ==== Textbooks ====
-The required textbook for this course is
+The required textbook is: Computer Vision Algorithms and Applications, Richard Szeliski, Springer, 2011.
+  * Hardcopy: available at the York Bookstore; one copy is on reserve at the Steacie Library.
+  * [[http://szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf|Online version]]
+  * [[https://sites.google.com/site/szeliskijp/book/eratta|Errata]]
-Computer Vision Algorithms and Applications
+Supplementary (Optional):
-by Richard Szeliski, Springer, 2011.
+  * Multiple View Geometry in Computer Vision, Hartley R & Zisserman A, 2004
+  * Pattern Recognition and Machine Learning, Bishop CM, 2006
+  * [[http://www.computervisionmodels.com/|Computer Vision:  Models, Learning and Inference, Prince SJD, 2012]]
-Errata for the textbook is available [[https://sites.google.com/site/szeliskijp/book/eratta|here]].
+==== Lectures ====
-This text is available at the York University Bookstore in York Lanes. Also, a copy is on reserve at the Steacie Library on campus.
+    * MW 10:00AM - 11:30AM in Calumet 106.
+    * Students are responsible for all material covered in lectures.
+    * Lecture slides will be posted incrementally on this website.
-==== Workload ====
+==== Assigned Readings ====
-    * Lectures: Students are responsible for all material covered in lectures. Lecture slides will be posted incrementally on this website; see the Schedule link on the side bar to this page.
     * Assigned Readings: Students are responsible for all material assigned as reading in the textbook; see the Schedule link on the side bar to this page.
-    * Labs: There will be six two-hour labs, these will be held at 4pm-6pm on selected Mondays; see the Schedule link on the side bar to this page. The labs will be laptop-based:  please bring your own laptop, or sign one out from the department.  The primary software environment will be MATLAB.  The TA will be present at each lab to provide demonstrations and guidance.  Students are responsible for all material presented in labs. Labs 1, 2, 4 and 5 will be associated with the four short assignments (see below). Lab 3 will be used to help students prepare for the midterm. The final lab will be used to demo projects and to discuss project reports.
-    * Assignments: There will be four short assignments that include theory and coding questions; details will be posted incrementally on this website; see the Schedule link on the side bar to this page.
+==== Labs ====
-    * Midterm: In class, closed book.
-    * Project: Students will complete a project involving the implementation of a computer vision algorithm of their choosing. Details can found under the Project link in the side bar.
+    * Six two-hour labs held in Bergeron 211.
+    * 4pm-6pm on selected Mondays - see schedule.
+    * Laptop-based:  please bring your own laptop, or sign one out from the lab monitor in LAS 1006. See https://wiki.eecs.yorku.ca/dept/tdb/services:loaner-laptop for more information.
+    * Desks do not have power - please make sure laptop batteries are fully charged or bring a long power cable to plug into the wall.
+    * Primary software environment:  MATLAB.  York now has a site license - please see https://matlab.info.yorku.ca/ for information on how to install MATLAB on your machine.
+    * The TA will be present at each lab to provide demonstrations and guidance.
+    * Students are responsible for all material presented in labs.
+    * Labs 1, 2, 4 and 5 will be associated with the four short assignments (see below).
+    * Lab 3 will be used to help students prepare for the midterm.
+    * The final lab will be used to demo projects and to discuss project reports.
+==== Assignments ====
+    * There will be four short assignments that include theory and coding questions
+    * Due dates can be found on the schedule page.
+==== Midterm ====
+    * In class, closed book.
+    * Lab 3 will be used to help students prepare.
+==== Project ====
+    * Students will complete a project involving the implementation of one or more  computer vision algorithms of their choosing.
+    * Details can be found on the project page.
 ==== Course Learning Outcomes ====