Dr Jing Wu

Lecturer

School of Computer Science and Informatics

Email:: wuj11@cardiff.ac.uk
Telephone:: +44 (0)2920 688810

: Available for postgraduate supervision

I am a lecturer in the School of Computer Science and Informatics at Cardiff University, and a member of the Visual Computing research group. I received PhD from the University of York, United Kingdom, with thesis on statistical approaches to gender classification in the surface normal domain. I received MSc and BSc in Computer Science from Nanjing University, China.

My research interests lie in the area of 3D visual reconstruction and its application, such as face recognition, bas-relief modelling. I currently have particular interests in image-based high resolution surface reconstruction, 3D face reconstruction and transformation, and visual SLAM, and looking into interdisciplinary applications in engineering and medicine.

Education and qualifications

2009: PhD (Computer Science), University of York, York, UK
2005: MSc (Computer Science and Technology), Nanjing University, Nanjing, China
2002: BSc (Computer Science and Technology), Nanjing University, Nanjing, China

Career overview

2016 - present: Lecturer, School of Computer Science and Informatics, Cardiff University
2009 - 2016: Research Associate, School of Computer Science and Informatics, Cardiff University

Honours and awards

TAROS Best Paper Award, 2018
BMVC Best Security Paper Prize, 2007
Overseas Research Students Awards Scheme (ORSAS), UK, 2005 - 2008

Professional memberships

Member of ACM, IEEE, BMVA, EG
HEA Fellowship

2019

Xiang, S.et al. 2019. Interactive correction of mislabeled training data. Presented at: IEEE VIS 2019, Vancouver, BC, Canada, 20-25 October 2019.
Wang, X.et al. 2019. Discriminative features matter: Multi-layer bilinear pooling for camera localization. Presented at: BMVC 2019: 30th British Machine Vision Conference, Cardiff, UK, 9-12 September, 2019.
Zhang, Y.et al. 2019. Computer-assisted relief modelling: a comprehensive survey. Presented at: Eurographics Conference 2019 STARs, Genova, Italy, 6-10 May 2019.

2018

Wu, J. and Ji, Z. 2018. Seeing the unseen: Locating objects from reflections. Presented at: 19th Towards Autonomous Robotic Systems (TAROS) Conference, Bristol, UK, 25- 27 July 2018.

2017

Liu, S.et al. 2017. Visual diagnosis of tree boosting methods. IEEE Transactions on Visualization and Computer Graphics 24(1), pp. 163-173. (10.1109/TVCG.2017.2744378)

2016

Wu, J.et al. 2016. Improving shape from shading with interactive Tabu search. Journal of Computer Science and Technology 31(3), pp. 488-500. (10.1007/s11390-016-1639-1)

2014

Wu, J.et al. 2014. Use of non-photorealistic rendering and photometric stereo in making bas-reliefs from photographs. Graphical Models 76(4), pp. 202-213. (10.1016/j.gmod.2014.02.002)

2013

Wu, J.et al. 2013. Making bas-reliefs from photographs of human faces. Computer-Aided Design 45(3), pp. 671-682. (10.1016/j.cad.2012.11.002)

2012

Zhang, L., Hancock, E. R. and Wu, J. 2012. Estimating surface characteristics and extracting features from polarisation. Presented at: Joint IAPR International Workshop, SSPR&SPR 2012, Hiroshima, Japan, November 7-9, 2012 Presented at Gimel'farb, G. et al. eds.Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, SSPR & SPR 2012, Hiroshima, Japan, November 7-9, 2012, Proceedings.. Lecture Notes in Computer Science Vol. 7626. Springer Berlin Heidelberg: Springer pp. 400-408., (10.1007/978-3-642-34166-3_44)

2011

Wu, J., Smith, W. A. P. and Hancock, E. R. 2011. Gender discriminating models from facial surface normals. Pattern Recognition 44(12), pp. 2871-2886. (10.1016/j.patcog.2011.04.013)
Kawulok, M., Wu, J. and Hancock, E. R. 2011. Supervised relevance maps for increasing the distinctiveness of facial images. Pattern Recognition 44(4), pp. 929-939. (10.1016/j.patcog.2010.10.010)
Zhang, Z., Hancock, E. R. and Wu, J. 2011. An information theoretic approach to gender feature selection. Presented at: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, Spain, 6-13 Nov 20112011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). Piscataway, N.J.: IEEE pp. 1425-1431., (10.1109/ICCVW.2011.6130418)

2010

Wu, J., Smith, W. A. P. and Hancock, E. R. 2010. Facial gender classification using shape-from-shading. Image and Vision Computing 28(6), pp. 1039-1048. (10.1016/j.imavis.2009.09.003)
Wu, J., Smith, W. A. P. and Hancock, E. R. 2010. Semi-supervised feature selection for gender classification. Presented at: 9th Asian Conference on Computer Vision, Xi’an, China, 23-27 September 2009 Presented at Zha, H., Taniguchi, R. and Maybank, S. eds.Computer Vision – ACCV 2009: 9th Asian Conference on Computer Vision, Xi’an, September 23-27, 2009, Revised Selected Papers, Part II, Vol. II. Lecture Notes in Computer Science Vol. 5995. Berlin Heidelberg: Springer pp. 23-33., (10.1007/978-3-642-12304-7_3)

2009

Wu, J.et al. 2009. Extracting gender discriminating features from facial needle-maps. Presented at: 2009 IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, 7-10 Nov 20092009 IEEE International Conference on Image Processing: Proceedings. Piscataway, NJ: IEEE pp. 2449-2452., (10.1109/ICIP.2009.5414129)

2008

Wu, J., Smith, W. A. P. and Hancock, E. R. 2008. Supervised principal geodesic analysis on facial surface normals for gender classification. Presented at: Structural, Syntactic, and Statistical Pattern Recognition Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, 4-6 December 2008 Presented at da Vitoria Lobo, N. et al. eds.Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings. Lecture Notes in Computer Science Vol. 5342. Berlin Heidelberg: Springer pp. 664-673., (10.1007/978-3-540-89689-0_70)
Wu, J., Smith, W. A. P. and Hancock, E. 2008. Gender classification based on facial surface normals. Presented at: 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, Florida, 8-11 December 200819th International Conference on Pattern Recognition (ICPR 2008). Piscataway, NJ: IEEE pp. 1-4., (10.1109/ICPR.2008.4761056)
Wu, J., Smith, W. and Hancock, E. 2008. Gender classification based on facial surface normals. Presented at: International Conference on Pattern Recognition, Tampa, FL., 8-11 Dec 200819th International Conference on Pattern Recognition : (ICPR 2008) ; Tampa, Florida, USA 8-11 December 2008.. Piscataway, N.J.: IEEE pp. 1-4., (10.1109/ICPR.2008.4761056)
Wu, J., Smith, W. A. P. and Hancock, E. R. 2008. Facial gender classification using shape from shading and weighted principal geodesic analysis. Presented at: 5th International Conference, ICIAR 2008, Póvoa de Varzim, Portugal, 25-27 June 2008 Presented at Campilho, A. and Kamel, M. eds.Image Analysis and Recognition: 5th International Conference, ICIAR 2008, Póvoa de Varzim, Portugal, June 25-27, 2008. Proceedings.. Lecture Notes in Computer Science Vol. 5112. Berlin Heidelberg: Springer pp. 925-934., (10.1007/978-3-540-69812-8_92)
Wu, J., Smith, W. A. P. and Hancock, E. R. 2008. Weighted principal geodesic analysis for facial gender classification. Presented at: 12th Iberoamericann Congress on Pattern Recognition, CIARP 2007, Valparaiso, Chile, 13-16 November 2007 Presented at Rueda, L., Mery, D. and Kittler, J. eds.Progress in Pattern Recognition, Image Analysis and Applications: 12th Iberoamericann Congress on Pattern Recognition, CIARP 2007, Valparaiso, Chile, November 13-16, 2007. Proceedings.. Lecture Notes in Computer Science Vol. 4756. Berlin Heidelberg: Springer pp. 331-339., (10.1007/978-3-540-76725-1_35)

2007

Wu, J., Smith, W. A. and Hancock, E. R. 2007. Gender classification using shape from shading. Presented at: BMVC 2007, Warwick, UK, 10-13 September 2007 Presented at Rajpoot, N. M. and Bhalerao, M. L. eds.Proceedings of the British Machine Conference. BMVA Press pp. 50.1-50.10., (10.5244/C.21.50)
Dickens, M. P.et al. 2007. Face recognition using principal geodesic analysis and manifold learning. Presented at: Third Iberian Conference, IbPRIA 2007, Girona, Spain, 6-8 June 2007 Presented at Martí, J. ed.Pattern Recognition and Image Analysis: Third Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I, Vol. 4477. Lecture Notes in Computer Science Vol. 4477. Berlin Heidelberg: Springer pp. 426-434., (10.1007/978-3-540-72847-4_55)
Wu, J., Smith, W. A. P. and Hancock, E. R. 2007. Learning mixture models for gender classification based on facial surface normals. Presented at: Third Iberian Conference, IbPRIA 2007, Girona, Spain, 6-8 June 2007 Presented at Marti, J. et al. eds.Pattern Recognition and Image Analysis: Third Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I, Vol. 4477. Lecture Notes in Computer Science Vol. 4477. Springer Berlin Heidelberg pp. 39-46., (10.1007/978-3-540-72847-4_7)

2006

Wu, J., Smith, W. A. P. and Hancock, E. 2006. Gender classification using principal geodesic analysis and gaussian mixture models. Lecture Notes in Computer Science 4225, pp. 58-67. (10.1007/11892755_6)

In the 2019/20 academic year, I am involved in the teaching of the following modules:

CM1101 Computational Thinking
CM1103 Problem Solving with Python
CM3203 One Semester Individual Project
CMT400 Dissertation

My main research interest is image-based 3D reconstruction. To reconstruct 3D information from 2D is a low-level vision problem, and assists many mid- and high-level vision tasks, such as segmentation, tracking, recognition, etc. and also has applications in computer graphics. I am working / have worked on a number of projects in this regard, including:

Learning-based and 3D assisted caricaturization of multi-modal portraits, PI, Travel fund to visit Nanjing University. Apr 2018 - Apr 2020.
Pushing the boundary of vision-based 3D surface imaging, CoI, Renishaw and Cardiff University Strategic Fund. Apr 2018 - Mar 2019.
Realistic SFS with user interaction, which developed an interactive framework to tackle intrinsic problems of SFS, and combined heuristic search to improve the intuitiveness of user interaction. It is an EPSRC project.
Generating bas-reliefs from face photographs, which developed a framework combining techniques of machine learning, SFS, photometric stereo, and non-photorealistic rendering etc. to tackle the problem of bas-relief generation from a single input face image. It is part of a RIVIC (The Welsh Research Institute of Visual Computing) scienfic programme - Vision-based Geometric Modelling.
SFS in facial gender classification, which proposed a shape-from-shading (SFS) based representation that can implicitly encode both the 2D texture and the 3D shape information to improve facial gender classification using either information alone.