Academic Profile

Academic Profile

Assoc Prof Cham Tat Jen


Associate Professor

School of Computer Science and Engineering
College of Engineering

Email: ASTJCHAM@NTU.EDU.SG
Phone: (+65)6790 6230
Office: N4-02a-07

Education
  • PhD University of Cambridge 1996
  • BA(Eng)(Hons) University of Cambridge 1993
Biography
Tat-Jen is an Associate Professor in the School of Computer Science & Engineering, Nanyang Technological University. He received his BA in Engineering in 1993 and his PhD in 1996, both from the University of Cambridge. Tat-Jen was subsequently conferred a Jesus College Research Fellowship in Science in 1996-97. From 1998 to 2001, he was a research scientist at DEC/Compaq Research Lab in Cambridge, MA, USA. After joining NTU in 2002, he was concurrently a Faculty Fellow in the Singapore-MIT Alliance Computer Science Program in 2003-2006.

In research., Tat-Jen received overall best paper prizes at PROCAMS’05, BMVC’94, and in particular at ECCV'96, while his PhD student Minh-Tri Pham was awarded the PREMIA 2nd best student paper prize for their ICCV'2007 paper. Tat-Jen is an inventor on eight patents. He is currently a co-Principal Investigator in the NRF BeingTogether Centre (BTC) on 3D Telepresence, a collaboration between NTU and UNC at Chapel Hill.
Tat-Jen is on the editorial board for the International Journal of Computer Vision (IJCV). He has been a General Chair for ACCV’14, Area Chair for ICCV'09, ACCV’07, ICCV’05 and ACCV’06, Associate Editor for IJIG and IPSJ-CVA, a Program Chair for MMM’07, and a co-founder for the PROCAMS workshop series in 2003. Nationally, he has been on various review panels for A*STAR and the National Research Foundation (NRF). Tat-Jen has served for a number of terms on the NTU Senate, and previous roles held include being the Director for the Centre for Multimedia & Network Technology (CeMNet) and an affiliate faculty with the Singapore-ETH Centre’s Future Cities Lab.

Tat-Jen’s research interests are broadly in computer vision and machine learning. Currently, his BTC team has focused on high-fidelity 3D dynamic reconstruction of humans and room environments with casually placed sensors, via deep learning approaches for semantic understanding to enable accurate reconstruction in the presence of clutter, occlusion and limited sensor coverage. His previous work includes image-based localization in urban environments, object matching and registration, human tracking, activity recognition, as well as projector-camera systems to turn all surfaces into ubiquitous interactive displays.
Research Interests
Tat-Jen’s research interests are broadly in computer vision and machine learning. Currently, his BTC team has focused on high-fidelity 3D dynamic reconstruction of humans and room environments with casually placed sensors, via deep learning approaches for semantic understanding to enable accurate reconstruction in the presence of clutter, occlusion and limited sensor coverage. His previous work includes image-based localization in urban environments, object matching and registration, human tracking, activity recognition, as well as projector-camera systems to turn all surfaces into ubiquitous interactive displays.
Current Projects
  • Advanced Technologies for 3D Capture, Communication and Display
  • BeingTogether
  • Human Gait Recognition with Statistical Learning
  • Novel Scene Acquisition and Display Technologies for a Next-Generation Room-Based Telepresence System
  • Project Tacrea
  • Project image understanding - developing automatic target detection and recognition capability
  • SMART Space
  • Singapore – ETH Centre (SEC) for Global Environmental Sustainability: Future Cities Laboratory (FCL) programme
  • Vision Based Crowd Analysis
Selected Publications
  • Tat-Jen Cham, Ciptadi Arridhana, Wei-Chian Tan, Minh-Tri Pham, Liang-Tien Chia. (2010). Estimating Camera Pose from a Single Urban Ground-View Omnidirectional Image and a 2D Building Outline Map. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
  • Minh-Tri Pham Viet-Dung D. Hoang Tat-Jen Cham. (2008). Detection with Multi-exit Asymmetric Boosting. (pp. 1 - 8).
  • D. Xu, T.J. Cham, S. Yan and S.-F. Chang. (2008). IEEE International Conference on Computer Vision and Pattern Recognition: Near Duplicate Image Identification with Spatially Aligned Pyramid Matching.
  • Minh-Tri Pham Tat-Jen Cham. (2007, October). Fast Training and Selection of Haar features using Statistics in Boosting-based Face Detection. Paper presented at 11th IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil.
  • C.K.Yeo, L.T.Chia, T.J.Cham, R.Deepu. (2007). IEEE International Conference on Multimedia and Expo (ICME): Click4BuildingID@NTU: Click for Building Identification with GPS-enabled Camera Cell Phone.Beijing, China: IEEE.

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