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Dr. CHAN Kwok Leung (陳國良博士)

MSc(Wales), PhD(Wales)
CEng, MIET

Assistant Professor

Contact Information

Office: G6407 AC1
Phone: 34427133
Fax: 34420562
Email: itklchan@cityu.edu.hk

Research Interests

  • Computer Vision, Image Processing
K. L. Chan received his MSc degree in Electronics from the University of Wales Institute of Science and Technology, U.K. and PhD degree from the University of Wales College of Medicine, U.K. He is currently an Assistant Professor of the Department of Electronic Engineering, the City University of Hong Kong. His research interests include computer vision and image processing.


Research Grants

  • Visual information understanding framework with human perception model and machine learning, General Research Fund, Research Grants Council, Amount: HKD $308,228, 1 Jan 2020 - 31 Dec 2021, K L Chan (PI), T Tjahjadi (Co-I).


Publications Show All Publications Show Prominent Publications


Journal

  • Chan, K. L. (2021). A foveated vision framework for visual change detection using motion and textural features. Signal, Image and Video Processing. doi:10.1007/s11760-020-01823-z
  • Chan, K. L. (2018). Saliency detection in video sequences using perceivable change encoded local pattern. Signal, Image and Video Processing. Vol. 12, No. 5. 975 - 982. doi:10.1007/s11760-018-1242-8
  • CHAN, K. L. (2018). Segmentation of moving objects in image sequence based on perceptual similarity of local texture and photometric features. EURASIP Journal on Image and Video Processing. doi:10.1186/s13640-018-0308-4
  • Chan, K. L. (2015). Detection of foreground in dynamic scene via two-step background subtraction. Machine Vision and Applications. Vol. 26, No. 6. 723 - 740.
  • Chan, K. L. (2013). Detection of swimmer using dense optical flow motion map and intensity information. Machine Vision and Applications. Vol. 24, No. 1. 75 - 101.
  • Wong, S. S. & Chan, K. L. (2010). 3D object model reconstruction from image sequence based on photometric consistency in volume space. Pattern Analysis & Applications. Vol. 13, Issue 4. 437 - 450.

Conference Paper

  • Wang, J. & Chan, K. L. (Nov 2019). Background subtraction based on Encoder-Decoder Structured CNN. The 5th Asian Conference on Pattern Recognition. Auckland. New Zealand: .
  • Chan, K. L. (Nov 2019). Segmentation of foreground in image sequence with foveated vision concept. The 5th Asian Conference on Pattern Recognition. Auckland. New Zealand: .
  • Chan, K. L. (2018). Detection of change in video based on local pattern and photometric features. 26th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2018. Plzen. Czech Republic: .
  • Chan, K. L. (2017). Saliency/non-saliency segregation in video sequences using perception-based local ternary pattern features. 15th IAPR International Conference on Machine Vision Applications. (pp. 480 - 483). Nagoya. Japan: .
  • Chan, K. L. (2016). Background modelling using perception-based local pattern. 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2016. (pp. 253 - 260). Plzen. Czech Republic: .
  • Chan, K. L. (2013). Detection and decomposition of foreground target from image sequence. IAPR International Conference on Machine Vision Applications. (pp. 459 - 462). Kyoto. Japan: .
  • Chan, K. L. (2011). Detection of swimmer based on joint utilization of motion and intensity information. IAPR Conference on Machine Vision Applications. (pp. 450 - 453). Nara. Japan: .


External Services


Professional Activity

  • 2005 - Now, Professional Review Interviewer, IET.


Service in CityU


Administrative Assignment

  • Jul 2018 - Now, BEng in Computer and Data Engineering, Associate Programme Leader.


MSc dissertation [2021]

  • 1. Semantic segmentation with machine learning
    2. Saliency detection with deep learning
    3. Image dehazing via convolutional neural network


Directed Studies for Taught Postgraduate Students [2020]

    1. Gait-based gender classification
    2. Micro-expression recognition with deep learning
    3. Detection of subtle change in facial expression


Undergraduate Final Year Project

    1. Image dehazing with deep learning
    2. Vision-based gender and age classification
    3. Semantic segmentation with deep learning
    4. Saliency detection with machine learning


ITF Project

  • Project title: Smart Geotechnical Monitoring System


Last update date : 17 Dec 2020