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IEEE Fellow Associate Professor Lap-Pui Chau

Effective thereupon this year, NTU EEE’s Assoc Prof Lap-Pui Chau has been elevated by the IEEE Board of Directors to “IEEE Fellow”, with the following citation:

For contributions to fast computation algorithms for visual signal processing

Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to the title of “IEEE Fellow”. The IEEE Fellow distinction is conferred to select IEEE members whose record of extraordinary achievements – in any of the IEEE fields of interest – is recognised.

It is the highest grade of membership in the IEEE and less than 0.1% of voting members are selected annually for this member grade elevation.

We find out more from Prof Chau about his current projects and his thoughts on earning the IEEE Fellow title:

Professor Wang Peng
Prof Chau (2nd from the back right) is seen here at an
informal meal gathering with his research staff members

How do you feel & who would you like to thank?
“I feel honoured to be recognised by my peers from the IEEE and obtain this prominent achievement in my career. I want to thank all my teachers and mentors for guiding and motivating me to have further interests in scientific research.

I would also like to thank NTU EEE for providing me a platform with the opportunity to contribute in my research area! I have been with NTU for almost 20 years. My engagement in research works, together with contributions from all colleagues have created substantial research impact and recognition. Our research efforts help to bring NTU EEE to greater heights.”

 

 

What EEE-related projects are you currently involved in?

Firstly, Contrast Enhanced Vision for Deepwater Monitoring System: Novel optical characterisation with associated signal processing can enable dramatic increase in image and video sharpness and clarity under deepwater environment. This project will describe a feasible method to enhance deepwater optical image and video. Deepwater vehicles namely Remotely Operated Vehicles (ROV) generally come with optical sensors for their capability of remote operation. Therefore, deepwater vision is an important issue in maritime application.

Secondly, Development of NTU EEE/ NXP- Intelligent Transport Systems Test-Bed: Owing to the limited field of view of a single camera, a target’s information is no longer available once the target leaves the view of the camera. Hence, a network of cameras is usually required to cover wide areas. However, it is not always possible to have overlapping views by cameras. So, the observations of the same object can be widely separated in time and space in such a scenario. In this project, we would like to develop a real-time algorithm on our joint NTU-NXP Smart Mobility Test Bed to continuously track objects of interest, such as vehicles and humans.

Thirdly, Multi-sensory Audio-visual Analytics in Remote Sensing of Idling Engines: Under the Environment Protection and Management Act, the driver of every motor vehicle shall switch off the engine of the vehicle when it is stationary. However, there’s lack of evidence as errant drivers would switch off their engines upon the sighting of enforcement officers. Therefore, detecting and identifying the illegal activities is of great benefit to the reduction of labour costs and pollutant emission. We propose a framework for remotely detecting states that idle for 3 minutes or longer automatically using thermal imaging cameras.

Lastly, Video and Image Enhancement Using Rain, Haze and Fog Removal Techniques: With more of CCTV being installed, there is an increasing need to use video analytics to detect for unusual events. However, the performance of CCTV video analytics can be severely degraded under raining conditions due to rain streaks appearing in the scene. In our project, we develop a solution that is able to enhance the quality of outdoor video captured under raining conditions by removing the rain streaks and improving the contrast and sharpness of the captured video.

What should students do to prepare for their future?
“Our students need to learn how to be lifelong learners in order to prepare themselves for future challenges.”

How do you motivate your students?
“I tell them that setting goals and preparing themselves early pays; the sooner the better.”

 

Published on: 16-May-2017