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ABOUT TARS

DIRECTORS

Natasha Banerjee
Associate Professor
Computer Science
CV | Scholar
Sean Banerjee
Associate Professor
Computer Science
CV | Scholar

At the Terascale All-sensing Research Studio (TARS) at Clarkson University, we perform research in human-driven artificial intelligence using capture and analysis of dense multi-person interactions in online and real-world environments. Our studio houses two multi-modal sensing spaces---the Gazebo, a dense multi-modal sensing space consisting of 16 Kinect sensors, 192 226-FPS color cameras, 16 thermal cameras, 16 sEMG sensors, 16 AMD Ryzen machines each with a 1080 Ti GPU, and 24 Intel 6-core machines to study multi-person interactions, and the Cube, a space with 4 Kinects, 5 thermal cameras, and 4 226-FPS color cameras to study two-person interactions. It also houses two Kinova Gen3 robotic manipulators, one LoCoBot mobile robot manipulator, multiple lab-built drones, a lab-built walker robot, and several VR systems, 3D printers, 3D scanners, a compute cluster with 275,000+ CUDA cores and 4,800+ Tensor cores spread over 50+ GPUs, and a 1 petabyte data center. The core of our work is in understanding how humans perform tasks in the real-world, to inform next generation artificial intelligence (AI), robotics, and virtual reality. Our research spans computer vision, deep learning, computer graphics, and human-computer interaction. The studio is funded through multiple NSF grants.

We look for graduate and undergraduate students with excellent academic credentials, substantial project work in computer science and AI (at the graduate level) and a strong drive to perform research with us. Contact either Dr. Sean Banerjee (sbanerje a clarkson d edu) or Dr. Natasha Banerjee (nbanerje a clarkson d edu) to determine research opportunities with the studio, or to schedule a visit.

SELECT PUBLICATIONS

VR / AR. R. Miller, N. K. Banerjee, and S. Banerjee (2022). Combining Real-World Constraints on User Behavior with Deep Neural Networks for Virtual Reality (VR) Biometrics. IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR).

[PDF]  [Video]  [Code]

VR / AR. R. Miller, N. K. Banerjee, and S. Banerjee (2022). Temporal Effects in Motion Behavior for Virtual Reality (VR) Biometrics. IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR).

[PDF]  [Video]  [Code]

VR / AR. R. Miller, N. K. Banerjee, and S. Banerjee (2022). Using External Video to Attack Behavior-Based Security Mechanisms in Virtual Reality (VR). IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR).

[PDF]  [Video]  [Code]

3D PRINTING + SCANNING. N. Lamb, N. Wiederhold, B. Lamb, S. Banerjee, and N. K. Banerjee (2021). Using Learned Visual and Geometric Features to Retrieve Complete 3D Proxies for Broken Objects. ACM Symposium on Computational Fabrication (SCF).

[PDF]  [Code]

VR / AR. R. Miller, N. K. Banerjee, and S. Banerjee (2021). Using Siamese Neural Networks to Perform Cross-System Behavioral Authentication in Virtual Reality. IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR).

[PDF]

VR / AR. R. Miller, N. K. Banerjee, and S. Banerjee (2020). Within-System and Cross-System Behavior-Based Biometric Authentication in Virtual Reality. IEEE Conference on Virtual Reality and 3D User Interfaces Workshops (VRW), Atlanta, Georgia.

[PDF]

VR / AR. J. Gately, Y. Liang, M. K. Wright, N. K. Banerjee, S. Banerjee, and S. Dey (2020). Automatic Material Classification Using Thermal Finger Impression. International Conference on Multimedia Modeling (MMM), Daejeon, Korea.

[PDF]

VR / AR. R. Miller, A. Ajit, N. K. Banerjee, and S. Banerjee (2019). Realtime Behavior-Based Continual Authentication of Users in Virtual Reality Environments. IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), San Diego, California.

[PDF]  [Video]

VR / AR. A. Ajit, N. K. Banerjee, and S. Banerjee (2019). Combining Pairwise Feature Matches from Device Trajectories for Biometric Authentication in Virtual Reality Environments. IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), San Diego, California [Best Student Paper].

[PDF]

3D PRINTING + SCANNING. N. Lamb, S. Banerjee, and N. K. Banerjee (2019). Automated Reconstruction of Smoothly Joining 3D Printed Restorations to Fix Broken Objects. ACM Symposium on Computational Fabrication (SCF), Pittsburgh, Pennsylvania.

[PDF]  [Presentation]  [Video]

ASSISTIVE AI. Y. Jiang, S. Banerjee, and N. K. Banerjee (2019). Predicting Human Grasp Locations on Cup Handles by Using Deep Neural Networks to Infer Heat Signatures from Depth Data. IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Shanghai, China.

[PDF]

ASSISTIVE AI. J. Ryan, S. Inzerillo, J. Helmick, A. Boolani, N. K. Banerjee, and S. Banerjee (2019). Predicting If Older Adults Perform Cognitive Tasks Using Body Joint Movements From RGB-D Videos. The Eleventh International Conference on eHealth, Telemedicine, and Social Medicine (eTELEMED), Athens, Greece.

[PDF]

VR / AR. A. Kupin, B. Moeller, N. K. Banerjee, and S. Banerjee (2019). Task-Driven Biometric Authentication of Users in Virtual Reality (VR) Environments. International Conference on Multimedia Modeling (MMM), Thessaloniki, Greece [Best Paper Candidate].

[PDF]

ASSISTIVE AI. Y. Jiang, E. Schenck, S. Kranz, S. Banerjee, and N. K. Banerjee (2019). CNN-Based Non-Contact Detection of Food Level in Bottles from RGB Images. International Conference on Multimedia Modeling (MMM), Thessaloniki, Greece.

[PDF]

ASSISTIVE AI. Y. Jiang, M. Luo, S. Banerjee, and N. K. Banerjee (2018). When Will Breakfast Be Ready: Temporal Prediction of Food Readiness Using Deep Convolutional Neural Networks on Thermal Videos. IEEE Intl. Conf. on Multimedia and Expo Workshops (ICMEW), San Diego, CA.

[PDF]

VR / AR. T. Dunn, S. Banerjee, and N. K. Banerjee (2018). User-Independent Detection of Swipe Pressure using a Thermal Camera for Natural Surface Interaction. International Workshop on Multimedia Signal Processing (MMSP), Vancouver, Canada [Top 5% Paper Award].

[PDF]

MULTI-SENSOR SYSTEMS. Y. Jiang, D. Russell, T. Godisart, N. K. Banerjee, and S. Banerjee (2018). Hardware Synchronization of Multiple Kinects and Microphones for 3D Audiovisual Spatiotemporal Data Capture. IEEE International Conference on Multimedia and Expo (ICME), San Diego, California.

[PDF]

MULTI-SENSOR SYSTEMS. L. Guo, H. Quant, N. Lamb, B. Lowit, N. K. Banerjee, and S. Banerjee (2018). Multi-Camera Microenvironment to Capture Multi-view Time-lapse Videos for 3D Analysis of Aging Objects. International Conference on Multimedia Modeling (MMM), Bangkok, Thailand.

[PDF]  [Video]

MULTI-SENSOR SYSTEMS. L. Guo, H. Quant, N. Lamb, B. Lowit, S. Banerjee, and N. K. Banerjee (2018). Spatiotemporal 3D Models of Aging Fruit from Multi-View Time-Lapse Videos. International Conference on Multimedia Modeling (MMM), Bangkok, Thailand.

[PDF]

3D PRINTING + SCANNING. N. Lamb, N. K. Banerjee, and S. Banerjee (2018). Programmatic 3D Printing of a Revolving Camera Track to Automatically Capture Dense Images for 3D Scanning of Objects. Intl. Conf. on Multimedia Modeling (MMM), Bangkok, Thailand.

[PDF]  [Video]

VR / AR. H. Quant, S. Banerjee, and N. K. Banerjee (2018). A virtual reality interface for interactions with spatiotemporal 3D data. International Conference on Multimedia Modeling (MMM), Bangkok, Thailand.

[PDF]  [Video]

APPLIED ML. D. Gwinn, J. Helmick, N. K. Banerjee, and S. Banerjee (2018). Optimal Estimation of Census Block Group Clusters to Improve the Computational Efficiency of Drive Time Calculations. Intl. Conf. on Geographical Information Systems Theory, Applications and Management (GISTAM), Madeira, Portugal.

[PDF]

APPLIED ML. T. Dunn, N. K. Banerjee, and S. Banerjee (2016). GPU acceleration of document similarity measures for automated bug triaging. International Workshop on Software Faults (co-located with IEEE International Symposium on Software Reliability Engineering, ISSRE), Ottawa, Canada.

[PDF]

PEOPLE

Natasha Banerjee
Associate Professor
Computer Science
Sean Banerjee
Associate Professor
Computer Science

PhD STUDENTS

Robert Miller
Computer Science
Nikolas Lamb
Computer Science
Noah Wiederhold
Computer Science
Xinchao Song
Computer Science
Priyo Ranjan Kundu Prosun
Computer Science
Gurpreet Kaur
Computer Science
Richard Turner
Computer Science
Mingjun Li
Computer Science
Joseph Judge
Computer Science

MS STUDENTS

Austin Dykeman
Computer Science
Owen Talmage
Computer Science
DiMaggio Paris
Computer Science
Alex Kupin
Computer Science

UNDERGRADUATE STUDENTS

Joshua Beha
Computer Engineering
Rosalina Delwiche
Computer Science
Chris Hickman
Computer Science
Cameron Hood
Computer Science
Alif Jakir
Computer Science
Collin Jamieson
Computer Engineering
Benjamin Lamb
Mechanical Engineering, RIT
Anthony Lombardi
Computer Science
Ben Molloy
Computer Science
Patrick O'Mahony
Computer Engineering
Holly Rossmann
Computer Science
Alaina Tulskie
Computer Science
Kaitlyn Witt
Computer Science

Copyright © Natasha Kholgade Banerjee. All rights reserved.