Bulk Sensors & Sensor Systems
Thrust Leader: Carey Rappaport, Northeastern University
This thrust is focused on designing and implementing novel bulk sensors and multi-sensor detection systems, including optimization of millimeter wave-based sensing of anomalies under clothing to detect explosives on and within the human body. Both portal and standoff systems will be considered. A testbed will be used to develop and evaluate multi-modal sensors and algorithms for Advanced Imaging Technology (AIT), enabling experimentation, model-based reconstruction, and automatic threat detection of explosives. We will investigate integration of trace and vapor detection sensors with bulk sensors into multi-modal AIT and standoff systems for explosives detection. Improved algorithms for existing bulk sensor systems and multi-modal fusion systems will be investigated in Thrust R4.
Faculty and Staff
- Galia Ghazi
- Yolanda Rodriguez-Vaqueiro
- Luis Tirado
- Pedro M. Fierro-Mercado
- William Ortiz
- Mike Collins
- Mike Woulfe
- Matthew Nickerson
- Greg Allan
- Tiphannie Zeng
- Nigil Lee
- Kitty Du
- Jenna Czech
- Alex Piers
- Thurston Brevett
- Diana Regalbuto
- Siddharth Velu
- Mohit Bhardwaj
- Shaan Patel
- Geometric image formation for target identification in mulit-energy computed tomography Tracey, B. and Miller, E., Proc. SPIE 8746, doi:10.1171/12.2020668, May 23, 2013.
- FBP-type image reconstruction algorithms for x-ray computerized tomography Z. Li PhD thesis, RPI .
- Analytic methods for SAR image formation & object classification in the presence of noise and clutter H. C. Yanik PhD thesis RPI .
- A New One-Class SVM for Anomaly Detection Y. Chen, J. Qian ICASSP 2013.
- Multi-Stage Classifier Design K. Trapeznikov, V. Saligrama, D. Castanon Machine Learning 2013.
- Joint Reconstruction and Segmentation of Electron tomography data Tuysuzoglu, W. C. Karl, D. A. Castanon, S. Unlu in Computational Imaging, C. A. Bouman, I. Pollak, P. J. Wolfe, editors, Proc. SPIE, Vol. 8657, SPIE, San Francisco, CA February 2013..
- Image Formation Methods for Dual Energy and Multi-Energy Computed Tomography Oguz Semerci PhD Thesis, Department of Electrical and Computer Engineering, Tufts University October 2012.
- Non-local means denoising of ECG signals Tracey and E. Miller IEEE Transactions on Biomedical Engineering, DOI 10.1109/TBME.2012.2208964, PMID 22829361 September 2012.
- Behavior Subtraction P. M. Jodoin, V. Saligrama, J. Konrad IEEE Trans. on Image Processing 2012.
- Video Anomaly Detection Based on Local Statistical Aggregates V. Saligrama, Z. Chen CVPR 2012.
- Sequential Decision System Design – (10/2013) Kirill Trapeznikov, Venkatesh Saligrama, David Castañón
- Simultaneous Learning of Related Tasks – (10/2013) Delaram Motamedvaziri, Venkatesh Saligrama, David Castañón
- Classification-Aware Methods for Explosives Detection Using Multi-Energy X-Ray Computed Tomography – (10/2013) Limor Martin, Prakash Ishwar, Clem Karl
- Cross-view Activity Recognition Using Hankelets – (10/2013) Binlong Li, Octavia L. Camps, Mario Sznaier
- Real-time Implementation of Automated Counter-flow Detection in Airport Security Exits – (10/2013) Mohamed A. Elgharib, Venkatesh Saligrama
- The Way They Move: Tracking Multiple Targets with Similar Appearance – (10/2013) Caglayan Dicle, Octavia Camps, Mario Sznaier
- Euclidean Structure Recovery from Motion in Prespective Image Sequences via Hankle Rank Minimization Mario Sznaier, Octavia Camps, Mustafa Ayazoglu
- Fluid Models for Dense Croed Tracking Oliver Lehmann, Gilead Tadmor
- Activity Recognition using Dynamic Subspace Angles Octavia Camps, Mario Sznaier, Binlong Li, Mustafa Ayazoglu, Teresa Mao, Necmiye Ozay
- Kernel Low-Rank Representation of Clustering and Classification Joseph Wang, Venkatesh Saligrama , David Castanon
Thrust 3 Projects
- Millimeter Wave Whole Body Scanning Radar Hardware for AIT R3-A1
- Computational Models and Algorithms for Millimeter Wave Whole Body Scanning for AIT R3-A2
- “Stand-off” and “On-the-Move” Detection of Security Threats R3-B1
- Advanced Imaging and Detection of Security Threats using Compressive Sensing R3-B2
- Standoff Detection of Explosives: IR Spectroscopy Chemical Sensing R3-C
- Magnetic Resonance Based Detection of Illicit Materials R3-D