Dr. Ming-Ching Chang

Chang, Ming-Ching

Video analytics, computer vision, and machine intelligence

The World Within Reach

 

Introduction

Dr. Ming-Ching Chang joined the Department of Computer Engineering as an assistant professor in 2016. His expertise includes video analytics, computer vision, and machine intelligence. After graduating from Brown University with a PhD, he worked as a computer scientist in the Computer Vision Lab of GE Global Research, where he was a member of the distinguished Visualization and Computer Vision (VCV) Group. Dr. Chang has worked on major external government programs, including the Defense Advanced Research Projects Agency.  He was also a Co-Principal Investigator for a series of programs awarded by the National Institute of Justice which focused on developing a group behavior recognition system that operates in unconstrained environments.

Prior to this faculty appointment, Dr. Chang was an adjunct instructor in the Department of Computer Science since 2012, where he taught advanced Artificial Intelligence courses. He has authored more than 35 peer-reviewed journal and conference publications and frequently serves as a reviewer for mainstream journals in the field.

Education

Ph.D., Laboratory for Engineering Man/Machine Systems, Division of Engineering, Brown University, USA

M.S., Computer Science and Information Engineering, National Taiwan University, Taiwan

B.S., Civil Engineering, National Taiwan University

Research Interests

Please visit Professor Chang's research website for information about his research: http://www.albany.edu/faculty/mchang2/.

Publications

Selected Journal Publications:

  1. L. Wen, Z. Lei, M.-C. Chang, H. Qi, and S. Lyu, “Multi-Camera Multi-Target Tracking with Space-Time-View Hypergraph”, to appear in International Journal of Computer Vision (IJCV) Special Issue, 2016.

  2. M.-C. Chang and B. B. Kimia, “Measuring 3D Shape Similarity by Graph-Based Matching of the Medial Scaffolds”, Computer Vision and Image Understanding (CVIU), , Special Issue on 3D Imaging and Modeling (3DIM), Elsevier, Vol. 115, Issue 5, pp. 707-720, May. 2011.

  3. M.-C. Chang, F. F. Leymarie, and B. B. Kimia, “Surface Reconstruction from Point Clouds by Transforming the Medial Scaffold”, Computer Vision and Image Understanding (CVIU), Elsevier, Vol. 113, Issue 11, pp. 1130-1146, Nov. 2009. (Top 5 downloaded computer science articles in ScienceDirect during April-June 2009.)

  4. M.-C. Chang, C.-S. Fuh, and H.-Y. Chen, “Fast Search Algorithms for Industrial Inspection”, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), World Scientific, Vol. 15, No. 4, pp. 675-690, 2001.

Selected Conference Publications:

  1. Y. Yang, M.-C. Chang, L. Wen, P. Tu, H. Qi, and S. Lyu, “Efficient Large-scale Photometric Reconstruction Using Divide-Recon-Fuse 3D Structure from Motion”, to appear in Advanced Video and Signal-based Surveillance (AVSS), 2016.

  2. X. Wang, M.-C. Chang, Y. Ying, and S. Lyu, “Co-regularized PLSA for Multi-Modal Learning”, to appear in AAAI Conference on Artificial Intelligence (AAAI), 2016 (acceptance rate 26%).

  3. M.-C. Chang, H. Qi, X. Wang, H. Cheng, and S. Lyu, “Fast Online Upper Body Pose Estimation from Video”, British Machine Vision Conference (BMVC), 2015 (acceptance rate 33%).

  4. Y. Kim, J. Chen, M.-C. Chang, E. M. Provost, X. Wang, and S. Lyu, “Joint Event Localization and Classification of Human Action Videos with Event Transitions”, IEEE Automatic Face and Gesture Recognition (FG), Oral presentation, 2015 (acceptance rate 12%).

  5. Y. Zhang, X. Liu, M.-C. Chang, W. Ge, and T. Chen, “Spacio-Temporal Phrases for Activity Recognition”, in Proceeding of European Conference on Computer Vision (ECCV), Firenze, Italy, Oct. 2012 (acceptance rate 25%).

  6. Y. Zhang, W. Ge, M.-C. Chang, and X. Liu, “Group-Level Context Learning for Event Recognition”, IEEE Workshop on Applications of Computer Vision (WACV), Oral presentation (acceptance rate 8%), Best Student Paper Award, Breckenridge, Colorado, USA, Jan. 2012.

  7. M.-C. Chang, N. Krahnstoever, and W. Ge, “Probabilistic Group-Level Mo(on Analysis and Scenario Recognition”, IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain, Nov. 2011 (acceptance rate 23.7%).

  8. N. Krahnstoever, M.-C. Chang, and W. Ge, “Gaze and Body Pose Estimation from a Distance”, IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), Best Paper Award - Runner up, Klagenfurt, Austria, Aug. - Sep. 2011.

  9. K. Sankaranarayanan, M.-C. Chang, and N. Krahnstoever, “Tracking Gaze Direction from Far-Field Surveillance Cameras”, IEEE Workshop on Applications of Computer Vision (WACV), Kona, Hawaii, USA, Jan. 2011.

  10. F. F. Leymarie, M.-C. Chang, C. Imielinska, and B. B. Kimia, “A General Approach to Model Biomedical Data from 3D Unorganised Point Clouds with Medial Scaffolds”, Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), Leipzig, Germany, July 2010.

  11. M.-C. Chang and B. B. Kimia, “Measuring 3D Shape Similarity by Matching the Medial Scaffolds”, 3-D Digital Imaging and Modeling (3DIM) in conjunction with IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan, pp. 1473-1480, Oct. 2009 (acceptance rate 45%).

  12. M.-C. Chang and B. B. Kimia, “Regularizing 3D Medial Axis Using Medial Scaffold Transforms”, IEEE Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, USA, pp. 1-8, June, 2008 (acceptance rate 32%).

  13. M.-C. Chang, F. F. Leymarie, and B. B. Kimia, “Surface Reconstruction from Point Clouds by Transforming the Medial Scaffold”, IEEE 3-D Digital Imaging and Modeling (3DIM), Montreal, Canada, pp.13-20, 2007.

  14. M.-C. Chang, F. F. Leymarie, and B. B. Kimia, “3D Shape Registration Using Regularized Medial Scaffolds”, oral presentation in IEEE 3D Data Processing, Visualization and Transmission (3DPVT), Thessaloniki, Greece, pp. 987-994, 2004.