Course Description

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''' Course Description'''
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''' Course Description'''  
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The course surveys recent developments in high level computer vision such as object recognition and categorization, action and event recognition, object tracking and human motion analysis, spatial and temporal reasoning for scene reconstruction and understanding, organization and indexing of visual data from large databases, mobile computer vision. The course also explores advanced classification and inference algorithms for high level visual tasks.
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The course surveys recent developments in high level computer vision such as object recognition and categorization, action and event recognition, object tracking and human motion analysis, spatial and temporal reasoning for scene reconstruction and understanding, organization and indexing of visual data from large databases, mobile computer vision. The course also explores advanced classification and inference algorithms for high level visual tasks.  
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<br>'''Requirements:'''
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<br>'''Requirements:'''  
Present 1-2 set of papers<br>Read papers and participate at class discussion during paper presentations<br>Course project: replicate existing methods or implement new research ideas.<br>  
Present 1-2 set of papers<br>Read papers and participate at class discussion during paper presentations<br>Course project: replicate existing methods or implement new research ideas.<br>  
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'''Grading policy:'''  
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'''Grading policy:'''
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Class participation &amp; discussion: 20%<br>Paper presentation (quality, clarity, depth, etc.): 30%<br>Course project (quality of the project presentation, work, writing, etc): 50%<br>  
Class participation &amp; discussion: 20%<br>Paper presentation (quality, clarity, depth, etc.): 30%<br>Course project (quality of the project presentation, work, writing, etc): 50%<br>  
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'''Prerequisites:'''
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'''Prerequisites:'''
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-&nbsp;<span style="line-height: 1.5em;">Some experience in research with one of the following fields: computer vision, image processing, computer graphics, machine learning.</span><br>
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- EECS 442 (Computer Vision) or equivalent
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- EECS 545 (Machine learning) or equivalent
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- MATLAB or equivalent programming experience is expected.
- MATLAB or equivalent programming experience is expected.

Revision as of 03:36, 22 September 2013

 Course Description

The course surveys recent developments in high level computer vision such as object recognition and categorization, action and event recognition, object tracking and human motion analysis, spatial and temporal reasoning for scene reconstruction and understanding, organization and indexing of visual data from large databases, mobile computer vision. The course also explores advanced classification and inference algorithms for high level visual tasks.


Requirements:

Present 1-2 set of papers
Read papers and participate at class discussion during paper presentations
Course project: replicate existing methods or implement new research ideas.


Grading policy:

Class participation & discussion: 20%
Paper presentation (quality, clarity, depth, etc.): 30%
Course project (quality of the project presentation, work, writing, etc): 50%


Prerequisites:

Some experience in research with one of the following fields: computer vision, image processing, computer graphics, machine learning.

- MATLAB or equivalent programming experience is expected.

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