About Me

I am a Research Fellow in the School of Information Technology at Deakin University, Australia. Before joining Deakin, I earned the Ph.D degree in Computer Science from The University of Warwick in 2017 and spent two years as an Associate Lecturer in Computing at Charles Sturt University, Australia. My research interests include Computer Vision, Machine Learning, Multimedia Forensics, and Autonomous Systems.


As a specialist in Multimedia Forensics, my most significant contribution is devising and enhancing various forms of device fingerprints (in form of statistical image features) and leveraging them as forensic tools to fight against cybercrimes. Through an EU project entitled "E!6687 FIIA – Forensic Image Identifier and Analyzer", I developed ground-breaking algorithms based on device fingerprints to cluster the millions of images in INTERPOL's Child Sexual Exploitation database to facilitate the identification of the offenders and victims of child sexual abuse on the Internet. The delivery of the project has helped INTERPOL identify thousands of offenders and victims of child sexual abuse over the past few years.


More recently, I have been intensively involved in research projects on Smart Video Surveillance and Precision Farming, enabled by the Internet of Things, Image/Video Processing, Computer Vision, and Machine Learning. As a key researcher, I participated in the project "R-DIPS: Real-time Detection of Concealment of Intent for Passenger Screening" funded by the UK Ministry of Defence and developed technologies that enable video surveillance systems at airports to perform across-camera multiple people tracking, trajectory forecasting, and abnormal behaviour analysis.


I also have strong interests in robotics and autonomous intelligent systems involving machine perception, SLAM, path planning, and navigation. Seeing artificial systems interacting autonomously and intelligently with human beings and our physical environment is fascinating. I firmly believe that, as technology evolves and matures, autonomous intelligent systems will become an indispensable part of our society and fundamentally change our day-to-day life in the near future.


Work is only a slice of life, not the entire pizza. In my spare time, I love to explore nature and appreciate the little beauty along the way. I am also an enthusiast of soccer and actively play in local football and fustal leagues. I recorded some videos for entertainment :) [Beat the bin.mp4] [Indoor juggling.mp4]


Education

Ph.D. in Computer Science
University of Warwick, UK, Mar. 2017
Thesis: Digital Image Forensics Based on Sensor Pattern Noise
M.E. in Signals & Information Processing
South China University of Technology, China, Sep. 2012
Thesis: Application of Digital Forensics in Image Source
Identification and Video Tampering Detection
B.E. in Electronic & Information Engineering
Hefei University of Technology, China, Sep. 2009

Publications

Journal Papers:


  • Self-Supervised Leaf Segmentation Under Complex Lighting Conditions

    Xufeng Lin, Chang-Tsun Li, Scott Adams, Abbas Kouzani, et al., Submitted to Pattern Recognition, 2022

    [Preprint] [Demo]

  • On the Detection-to-Track Association for Online Multi-object Tracking

    Xufeng Lin, Chang-Tsun Li, Victor Sanchez, and Carsten Maple, Pattern Recognition Letters, vol. 146, pp. 200-207, 2021.

    [Paper] [Demo] [Bibtex] [DOI]

  • Hybrid Clustering of Shared Images on Social Networks for Digital Forensics

    Rahimeh Rouhi, Flavio Bertini, Danilo Montesi, Xufeng Lin, Yijun Quan and Chang-Tsun Li, IEEE Access, vol. 7, pp. 87288-87302, 2019.

    [Paper] [Bibtex] [DOI]

  • A Fast Source-Oriented Image Clustering Method for Digital Forensics

    Chang-Tsun Li and Xufeng Lin, EURASIP Journal on Image and Video Processing: Special Issue on Image and Video Forensics for Social Media analysis, vol. 1, pp. 69–84, Oct. 2017.

    [Paper] [Bibtex] [DOI]

  • Large-Scale Image Clustering Based on Camera Fingerprints

    Xufeng Lin and Chang-Tsun Li, IEEE Transactions on Information Forensics and Security, 12(4):793- 808, 2017.

    [Paper] [Bibtex] [DOI]

  • Enhancing Sensor Pattern Noise via Filtering Distortion Removal

    Xufeng Lin and Chang-Tsun Li, IEEE Signal Processing Letters, 23(3):381-385, 2016.

    [Paper] [Bibtex] [DOI]

  • Preprocessing Reference Sensor Pattern Noise via Spectrum Equalization

    Xufeng Lin and Chang-Tsun Li, IEEE Transactions on Information Forensics and Security, 11(1):126-140, 2016.

    [Paper] [Bibtex] [DOI]


Conference Papers:


  • Constructing A Better Correlation Predictor for PRNU-based Image Forgery Localization

    Xufeng Lin and Chang-Tsun Li, IEEE International Conference on Multimedia and Expo (ICME2021), Shenzhen, China, July 5-9, 2021

    [Paper] [Bibtex] [DOI]

  • Deep Detection for Face Manipulation

    Disheng Feng, Xuequan Lu and Xufeng Lin, International Conference on Neural Information Processing (ICONIP), Bangkok, Thailand, 18-22 Nov, 2020

    [Paper] [Bibtex] [DOI]

  • Rotation-invariant Binary Representation of Sensor Pattern Noise for Source-Oriented Image and Video Clustering (Best Paper Award)

    Xufeng Lin and Chang-Tsun Li, IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Auckland, New Zealand, 27-30 Nov, 2018.

    [Paper] [Bibtex] [DOI]

  • Provenance analysis for instagram photos

    Yijun Quan, Xufeng Lin and Chang-Tsun Li, Australasian Conference on Data Mining, Bathurst, Australia, 28-30 Nov, 2018.

    [Paper] [Bibtex] [DOI]

  • Refining PRNU-Based Detection of Image Forgeries

    Xufeng Lin and Chang-Tsun Li, IEEE Digital Media & Academic Forum, Santorini, Greece, 4-6 Jul, 2016.

    [Paper] [Bibtex] [DOI]

  • Two Improved Forensic Methods of Detecting Contrast Enhancement in Digital Images

    Xufeng Lin and Chang-Tsun Li, SPIE International Conference on Media Watermarking, Security, and Forensics, San Francisco, California, US, 2-5 Feb, 2014.

    [Paper] [Bibtex] [DOI]

  • Exposing Image Forgery through the Detection of Contrast Enhancement

    Xufeng Lin, Chang-Tsun Li, and Yongjian Hu, IEEE International Conference on Image Processing, Melbourne, Australia, 15-18 Sep, 2013.

    [Paper] [Bibtex] [DOI]


Patents:


  • Clustering Images based on Camera Fingerprints (Granted on Jan, 2020.)

    Inventors: Xufeng Lin and Chang-Tsun Li


Book Chapters:


  • Image Provenance Inference Through Content-Based Device Fingerprint Analysis

    Xufeng Lin and Chang-Tsun Li, Computational Methods in Information Security: Algorithms, Technologies and Applications, ed. by A. I. Awad, N. Yen, and M. Fairhurst, Institution of Engineering and Technology (IET), 2017.

    [PDF] [Bibtex]


Professional Experience

Mar. 2019 - present:

Research Fellow in Biometrics and Forensics
School of Information Technology
Deakin University, Australia

Feb. 2017 - Jan. 2019 (2 years):
Associate Lecturer in Computing
School of Computing and Mathematics
Charles Sturt University, Australia

Apr. 2016 - Jul. 2016 (3 months):

Marie Curie Research Fellow
Research Center of Multimedia Information Security Detection and Intelligent Processing
South China University of Technology, China.
Funded by IDENTITY project through EU Horizon 2020-Marie Skodowska-Curie Actions-Research and Innovation Staff Exchange (RISE)

Nov. 2015 - Jan. 2016 (3 months):
Visiting Researcher and Developer
Videntifier Technologies
Reykjavík, Capital Region, Iceland

May 2015 - Jul. 2015(3 months):

Visiting Researcher
Multimedia Signal Processing and Security Lab (WaveLab)
University of Salzburg, Austria.
Funded by European Cooperation in Science and Technology (COST) Action IC1106

Apr. 2014 - May 2014 (2 months):
Marie Curie Visiting Researcher
Research Center of Multimedia Information Security Detection and Intelligent Processing
South China University of Technology, China.
Funded by DIVEFOR project through EU FP7 Marie Curie Actions - Industry-Academia Partnerships and Pathways (IAPP)

22-26 Jun, 2015 (1 week):

Trainee
The 12th International Summer School on Biometrics, Alghero, Italy
Funded by European Cooperation in Science and Technology (COST) Action IC1106

14-20 Jul, 2013 (1 week):
Trainee
The 7th International Computer Vision Summer School, Calabria, Italy
Funded by DIVEFOR project through EU FP7 Marie Curie Actions - Industry-Academia Partnerships and Pathways (IAPP)
Aug. 2011 - Jan. 2012 (6 months):
Software Engineer (Internship)
Oracle Research and Development Center
Shenzhen, Guangdong, China

Teaching

2019, Lecturer, Deakin University


2017-2019, Lecturer, Charles Sturt University


2012-2016, Tutor, University of Warwick


Academic Services

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