PROJECT TITLE: Educational application of computer vision & wearable sensors
PROJECT DESCRIPTION:
Despite the numerous education related researches going on in the world, researches are often lack data which has quantitative and physiological basis. This project suggests a solution by proving a quantitative and physiological platform via computer vision, and wearable sensors. The platform allows the design and execution of education related research to be taken with in a classroom.
Use an in class camera to monitor students through out classes. Simultaneously track student’s vitals (heart rate, blood pressure, brainwaves, etc) via wearable sensor. Identify each students using face recognition algorithm to match the data collected with individual students. External parameters such as exams grades, class grades, and survey’s conducted by students and professors are included in the feature space. Each students features are analysed via pattern recognition and machine learning algorithms.
This will provide a platform to study various education related research with quantitative and physiological basis.
Further application of the project could arise from the collection of massive student instructor data. This can be used for constructing predictive models. (Ex> based on the data collection of the past 1 year, is this student going to be successful with the final exam)
(Example, testing hypothesis of, do jokes by instructor in class room provide increased efficiency(heart rate, brain wave behavior)?)
PROJECT PERSONNEL:
David Sejin Park () ECE CBE
Mike Cheng () ECE
Vincent Luo () Biomedical Engineering
TEAMMATE RESPONSIBILITIES:
David will design the vision algorithms, and data processing.
Mike will design the software
Vincent will design the wearable sensors.
CAPSTONE SECTION RANKING:

Robotics, Vision and Virtual Medical Systems (Dana -- 332:438,478)

Communication (Rose -- 332:428)

Sensor, Control and DSP Systems (Pompili -- 332:418)

TEAMMATE QUALIFICATIONS:
Mike Cheng 332:452
David Park 332:422, 332:561, 198:535 (Pattern Recognition), (Data-mining and Algorithms)
PROJECT TITLE: Involvement map based on word mining algorithms and vision
PROJECT DESCRIPTION:
Rutgers is a vibrant community with many on going events, the project dual weids the tools of computer vision and word mining to show on going student activities on the web. Implement a real time map of Rutgers Campus centers, buildings and rooms with on going events via datamining on FB, Twitter, Tumblr (as well as location information - check in, etc). Perhaps implement a location sharing for students who downloads an app to support the above project. User feed back will be used to determine the credibility of the information that is being updated via machine learning algorithms.
Also, multiple cameras located at spatially varying places will be used to analyze movement of students to detect any extraordinary behaviors. Movements of students will be provided.
Potential extension of the project: If possible, implement multiple speakers across the campus to detect keywords that may indicate student activity. A socially meaningful analysis can be done via the information that are collected. Lots of students are taking the orgo exam) (privacy issues?)
PROJECT PERSONNEL:
David Sejin Park () ECE CBE
Mike Cheng () ECE
Sahir Jiwani () Industrial and Systems Engineering
TEAMMATE RESPONSIBILITIES:

David will design the vision algorithms (segmentation, motion tracking of students) datamining algorithms to determine on going behavior (assisted via IIE principles).

Mike Cheng will design the software

Sahir will design the flow map for analysing student movements captured via cameras.

CAPSTONE SECTION RANKING:
Robotics, Vision and Virtual Medical Systems (Dana -- 332:438,478)

Communication (Rose -- 332:428)

Computer Systems and Software &Financial Engineering (Parashar -- 332:438)
TEAMMATE QUALIFICATIONS:
Mike Cheng 332:452
David Park 332:422, 332:561, 198:535 (Pattern Recognition), (Data-mining and Algorithms)
PROJECT TITLE: Virtual Chalkboard
PROJECT DESCRIPTION:
Implement a cost effective way to create a digital whiteboard. Notes written on the whiteboard will be displayed on a website real time where students can easily see them via iphone, ipad or a laptop. This solves the issue where a student in the back of the room may not be able to see the whiteboard clearly in large lecture halls such as Arc 103. Machine Vision algorithms will be used to track the movements of the professor and to recognize the chalkboard via active vision. Speech recognition will be used to recognize the professor’s lecture, which will be placed as a transcript.
Future applications: If successfully implemented, this can be used as an online lecture generator.
PROJECT PERSONNEL:
David Sejin Park () ECE CBE
Mike Cheng () ECE
TEAMMATE RESPONSIBILITIES:
David will design the Means of detecting the chalk on the board, and also Motion Tracking
Mike will design the software
CAPSTONE SECTION RANKING:
Communication (Rose -- 332:428)
Robotics, Vision and Virtual Medical Systems (Dana -- 332:438,478)

Sensor, Control and DSP Systems (Pompili -- 332:418)

TEAMMATE QUALIFICATIONS:
Mike Cheng 332:452
David Park 332:422, 332:561, 198:535 (Pattern Recognition), (Data-mining and Algorithms)
PROJECT TITLE: Git Project Management Software
PROJECT DESCRIPTION:
Utilize the git revision control system to create an effective tool where people can collaborate on software. Current systems like GitHub.com charge teams for creating private repositories. The software will provide users with a free opensource project management tool to create closed sourced projects.
PROJECT PERSONNEL:
David Sejin Park ()
Mike Cheng () ECE
TEAMMATE RESPONSIBILITIES:
CAPSTONE SECTION RANKING:
c) Computer Systems and Software &Financial Engineering (Parashar -- 332:438)
TEAMMATE QUALIFICATIONS:
Mike Cheng 332:452