Research Assistant: Vision-based Human Activity Recognition using Deep Learning

Research Assistant (RA):
Vision-based Human Activity Recognition using Deep Learning

Number of Vacancies: 2

Available at 

Faculty of Engineering and Science,
Universiti Tunku Abdul Rahman (UTAR) KL Campus,
Jalan Genting Klang, 53300 Kuala Lumpur

Project Title

Vision-based Human Activity Recognition using Deep Learning

Project Leader

Dr. Tay Yong Haur (tayyh@utar.edu.my),
Department of Internet Engineering and Computer Science,
Faculty of Engineering and Science (FES), UTAR KL Campus.

Objective

Automated vision-based human activity recognition is one of the most active computer vision research topics. It has immense real-world applications, especially in security surveillance. Success implementation of this technology would lead to substantial improvement of public safety and security.

In this research, we will look into utilizing deep learning and convolution neural networks, and enhance it to model temporal information, as the fundamental components in this vision-based human recognition. We aim to devise a novel method to create a platform for applying machine learning in solving the very challenging vision-based human activity recognition.

Scope of Work

• To review the recent work in vision-based human activity recognition
• To devise and enhance deep learning model with temporal information
• To assess the performance of the model
• To create a proof-of-concept prototype of a human activity recognition applications

Job Description

• Remuneration of RM1500-2500 per month for 12 to 18 months, depending on experience.
• The RA must help the project leader in all works associated with the research.
• The RA must work closely with the sponsored industry partner to complete the research project.
• The RA may register for Master's degree by research or PhD program with UTAR.

Requirements

• Passionate in computer programming
• Have good mathematical foundations
• Strong interest and/or has working experience in machine learning/artificial intelligence/computer vision/image procession projects.
• Good English written and verbal communication
• Good analytical skills
• Self-motivated, requires minimal supervision, resourceful and willing to learn.
• Available to start working preferably on 1 May 2014.

Interested Candidate

If you are interested in the RA position advertised above, please email your CV directly to Dr. Tay Yong Haur (tayyh@utar.edu.my) as soon as possible. Feel free to write to Dr Tay for any further inquiry of the project.

Only short-listed candidates will be called for interview.