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Academic
Shin-Fang Ch'ng
Ph.D Student
Australian Institute for Machine Learning (AIML), University of Adelaide
Australian Centre for Robotic Vision (ACRV)
About Me
I am a Ph.D. researcher in the School of Computer Science, University of Adelaide, supervised by Prof. Tat-Jun Chin and Dr. Yasir Latif. I am affiliated with Australian Institute for Machine Learning (AIML) and Australian Centre for Robotic Vision (ACRV). My research interest is to develop robust/practical optimisation algorithms for robotic perception, with a particular focus on pose estimation and Structure-from-Motion (SfM)/Simultaneous Localisation and Mapping (SLAM) problems.
Interests
- Artificial Intelligence
- Computer Vision
- Optimisation
Education
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Ph.D in Mathematical & Computer Science, Present
The University of Adelaide
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BEng(Hons) in Electronic Systems Engineering, 2013
Sheffield Hallan University
Publications
Quantum Robust Fitting
We establish the practicability of a robust fitting formulation inspired by Fourier Analysis of Boolean functions and investigate a quantum algorithm to solve the formulation.
Resolving Marker Pose Ambiguity by Robust Rotation Averaging with Clique Constraints
We propose an efficient algorithm which exploit multiview consistencies to resolve marker pose ambiguities using rotation averaging.
Visual Localization Under Appearance Change: A Filtering Approach
We proposed a technique which exploit temporal continuity in visual localization for autonomous driving. We won the APRS/IAPR best paper award.
Outlier-Robust Manifold Pre-Integration for INS/GPS Fusion
We propose an efficient outlier-robust algorithm to tackle INS and GPS sensor fusion problem for pose estimation.
Contact
- Corner Frome Road and North Terrace, Adelaide, SA 5000