|Building: Lieb |
|Phone: +1 201 216 5611|
|Fax: +1 201 216 8249|
|School: Schaefer School of Engineering & Science|
|Department: Computer Science|
Ph.D. in Electrical Engineering University of
Southern California, Los Angeles, CA (2005)
M.S. in Electrical Engineering, University of Southern
California, Los Angeles, CA (2000)
Diploma in Electrical and Computer Engineering, Aristotle
University of Thessaloniki, Greece (1998)
- Binocular, multiple-view and video-based 3D reconstruction
- Perceptual organization
- 3D shape representation and object recognition
- Manifold learning
Assistant Professor, Dept. of Computer Science, Stevens Institute of Technology, 2008-present
- P. Mordohai and G. Medioni. (2006). "Tensor Voting: A Perceptual Organization Approach to Computer Vision And Machine Learning".
- P. Mordohai and G. Medioni. ""Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting", Journal of Machine Learning Research", vol. 11 411-450.
- M. Pollefeys, D. Nistér, J.-M. Frahm, A. Akbarzadeh, P. Mordohai, B. Clipp, C. Engels, D. Gallup, S.-J. Kim, P. Merrell, C. Salmi, S. Sinha, B. Talton, L. Wang, Q. Yang, H. Stewénius, R. Yang, G. Welch, H. Towles,. (2008). " "Detailed Real-Time Urban 3D Reconstruction From Video", International Journal of Computer Vision", vol. 78 (2-3), 143-167.
- A. Toshev, P. Mordohai and B. Taskar. (2010). "Detecting and Parsing Architecture at City Scale from Range Data", International Conference on Computer Vision and Pattern Recognition".
- X. Hu and P. Mordohai. (2010). "Evaluation of Stereo Confidence Indoors and Outdoors", International Conference on Computer Vision and Pattern Recognition".
- P. Mordohai. (2009). "The Self-Aware Matching Measure for Stereo", International Conference on Computer Vision".
- A. Patterson, P. Mordohai and K. Daniilidis. (2008). "Object Detection from Large-Scale 3D Datasets using Bottom-up and Top-down Descriptors", European Conference on Computer Vision".
- CS 537 Interactive Computer Graphics
- CS 559 Machine Learning: Fundamentals and Applications