- [Project title & Synopsis]
Computer Vision based Automatic Advertising System
- [Objectives & Deliverables]
We are aiming at developing & packaging a front-end system which automatically displays different types of advertisements (image or videos) according to the automatic monitoring of the statistics from the pedestrians (age and gender). These age and gender information is automatically obtained by computer vision algorithms by screening the frontal faces of the pedestrians. Specifically, we intend to develop a real-time system including real-time video acquisition, face detection, face feature extraction, age/gender estimation, decision and advertisement video/image display components.
- [Number of students needed for the project]
1 graduate or undergraduate student (full-time NUS student)
- [Prerequisites of the students]
The task for this internship is to develop the GUI, component-to-component interfaces as well as to implement the detection/estimation algorithm into C code from the MATLAB prototype. The intern student is required to be familiar with MATLAB environment, Windows C/C++, OpenCV platform, image/video processing programming. Experience in OpenGL, DirectX is a plus.
- [Project timeline]
The project will start from Mid-June and the student intern is expected to finish the system implementation at the end of August. The student is expected to work for another month in September to refine the system. The developing work mainly focuses on the interface design (the core component of the detection/estimation, feature extraction algorithms have already developed by the PhD students); therefore the work loading for the intern student is not high. The work will be conducted under the supervision of the PhD student therefore the student intern is highly expected to work cooperatively with the PhD student.
- [Whether work will be done]
Learning and Vision Group, Embedded Video Lab, E4-08-27, ECE, NUS
- [Contact]
Assistant Professor Dr. Yan Shuicheng,
[email protected]PhD Student Mr. Ni Bingbing,
[email protected]- [Daily Duty and Payment]
The student intern is expected to work from Monday to Friday for 8 hours per day. Please refer to the payment rate according to the department’s policy on part-time job for full time graduate/undergraduate stu