CISC 849: Big Data in Computer Vision
Department of Computer and Information Sciences
Class Time: Tue3:30pm- 6:30pm
Office Hours: To Be Announced
email: chandrak@udel.edu
phone: x8235
This class consists of advances in Big Data Computer Vision in the topics mentioned
below(but not limited to):
Feature and Information Extraction
Representation,Indexing,Storage,and Analysis
Automated 3D Modeling Pipelines
Multi-Modal Visual Sensor Data Fusion
Rendering and Visualization of Large-Scale Models
Semantic Labels and Imagery
2D and 3D Motion analysis methods
Video event detection and analysis
Incremental and online video event learning
Content-based video retrieval
Object/instance search video
Unconstrained video analysis(Web,Consumer,etc)
Social video analysis and topic mining
Video surveillance
Mobile-based video search and analysis
Benchmark 'Big' datasets
Grading
papers review(one per each class)30%
two short paper presentations(appx.20 minutes each)20%
one long paper(s) presentation(appx.75 minutes )30%
class participation(attendance,asking questions during presentations,etc)20%
Announcements:
Class on 3rd September re-scheduled for another day/time(announced later).
Next class will be on 10'th September
QA:
1. Do I need any background of computer vision?
Its ok if students have a solid math background and they are willing to self-study from a
computer vision book, etc.
2. Will a short introduction be given for each subject covered in this course?
Yes, I will give a short tutorial for each topic that I present. Students will do the same,
(Long paper presentations will have their own intro tutorial, etc)
3. Is there any requirements for the submitted review, such as the amount of words?
Yes,1.5 pages include references, etc.
4. Do I choose topics by myself or assigned by the professor?
I will work with the students and assign. So its a mutual decision.
5. Do students need to submit the paper review each time before class?
Yes, there will be penalty of 5% each late day.