NCSI: Development of Autonomous Unmanned Aerial Vehicle for Object Tracking and Following System

Status	Completed
Mentor Name	Jiang Lu
Mentor's XSEDE Affiliation	Campus Champion
Mentor Has Been in XSEDE Community	Less than 1 year
Project Title	Development of Autonomous Unmanned Aerial Vehicle for Object Tracking and Following System
Summary	The main focus of this project is to perform research, develop, implement, and evaluate solutions for Unmanned Aerial Vehicle (UAV) based object tracking and facial expression recognition (FER) application. In this project, we will use image/video processing techniques for moving object tracking and use deep learning for facial expression recognition. The students will also evaluate the tracking algorithms and FER in HPC. The implementation for the object tracking will lead to the study of an autonomous object following and human face expression recognition on UAV. The success of this system will lead to the applications of video processing to a wide range of robot control and perception problems.
Job Description	The students will be responsible for working a full semester for 10 hours per week. The students will participate in weekly group meetings for the monitoring of the project. The students will learn and implement object tracking algorithms with video processing. The students will evaluate the performance of the tracking algorithms in HPC based on XSEDE resources. The students will learn and program facial expression recognition in HPC. The students will have access to the center for robotic software at University of Houston Clear Lake. The students' final project will be used for a further research project in another semester.
Computational Resources	XSEDE training classes. XSEDE Bridges GPU Artificial Intelligence. XSEDE Bridges Pylon storage. AI/Deep learning software. Data visualization software. Image/video processing. Additionally, the mentor can use the resources in the center for robotic software at University of Houston Clear Lake.
Contribution to Community
Position Type	Apprentice
Training Plan	The student will be trained for the usage of XSEDE in University of Houston Clear Lake. The student will be supervised by the mentor and graduate students, who have research experience in Object Tracking and FER. The student will learn the basics of image/video processing with object tracking algorithms. The students will learn the basics of deep learning with facial expression recognition.
Student Prerequisites/Conditions/Qualifications	1. Interest and background in machine learning and artificial intelligence. 2. Thrive on the challenge in complex problem-solving. 3. Effective communication. 4. At least a strong background in one of the below, or a combination two having a solid background from the below list: Programming, Robotics, Mathematics, Data Analysis, and Visualization.
Duration	Semester
Start Date	01/22/2019
End Date	05/06/2019