CSCI 334301 Computer Vision, Fall 2014


Objectives

Computer vision is a discipline that studies how to teach computers to see. Computer vision has been widely used in our everyday life. Some examples are face detectors embedded in almost all the digital cameras, self-driving cars, apps that recognize objects from pictures, and the virtual display on the ground in a football game broadcasting. This course is to introduce principles and methods of computer vision. Topics include image features, image processing, shape analysis, image matching, camera model, depth image analysis, segmentation, motion, tracking, human pose detection, action detection, and object recognition. The prerequisite of the course is CS1. No image processing and Matlab experiences are required.

Time and Classroom

Tuesday and Thursday, 3:00 p.m. - 4:15 p.m. FULTON HALL 415.

Instructor

Hao Jiang, Room 568, Campanella Way 21, hjiang@cs.bc.edu, 617-552-8983.
Office hours: TBA.

Lecture Schedule (Approximate)

Week Date Topic
1 09/02/2014 : 09/04/2014 Introduction, Matlab Tutorial, Image Filtering  
2 09/09/2014 : 09/11/2014 Guest lecture (ECCV 2014)  
3 09/16/2014 : 09/18/2014 Image Features  
4 09/23/2014 : 09/25/2014 Shape  
5 09/30/2014 : 10/02/2014 Model Fitting  
6 10/07/2014 : 10/09/2014 Camera Model, Geometry and 3D Reconstruction  
7 10/14/2014 : 10/16/2014 Depth Sensors and RGBD Image Processing  
8 10/21/2014 : 10/23/2014 Segmentation  
9 10/28/2014 : 10/30/2014 Video Analysis, Motion  
10 11/04/2014 : 11/07/2014 Tracking  
11 11/11/2014 : 11/13/2014 Image Search and Retrieval  
12 11/18/2014 : 11/20/2014 Action Recognition  
13 11/25/2014 Pose Estimation  
14 11/29/2014 : 12/01/2014 Classifiers
15 12/02/2014 : 12/04/2014 Classifiers and Applications
16 12/09/2014 Final Project Mid-term Presentation

Grading
Textbook Reference books