MANTIS: A Multimodal Imaging Suite to Enhance Army s ISTAR Capabilities and Improve Soldiers Health

Abstract

This proposal requests support for the acquisition of a multimodal imaging suite, to acquire data to support ArmyÕs research in two areas: (i) Signal processing of big multimodal ISTAR data, and (ii) soldier healthcare. Termed MANTIS, this suite will comprise seven specialized optical imaging cameras covering wavelengths from the ultraviolet to long-wave infrared. MANTIS will release PI BajwaÕs research from the constraints of using publicly-available datasets, to create original experimental image data and introduce a Òclosed loopÓ approach to signal processing of modelÐvalidateÐrefine. Projects supported by MANTIS include (i) development of a novel data-adaptive union-of-subspaces model for analysis of big, dirty, multimodal image data, and (ii) human activity recognition based on multimodal image data generated by autonomous robots. MANTIS will also allow Co-PI Pierce to image biological tissues within previously inaccessible spectral windows and with unprecedented levels of resolution, speed, and sensitivity. In this area, MANTIS will support projects on rapid image-based assessment of burn injuries, diagnosis of infection, remote tagging and detection of chemical warfare agents, and studying the biological and physiological effects of closed head injury. MANTIS will also enable students to extend their research beyond post-processing of existing data, into the area of multimodal data acquisition. By designing multimodal experiments, then collecting and processing image data from MANTIS, students will gain expertise in the entire end-to-end process of big data acquisition and analysis. MANTIS will fill a critical need for the PI and the Co-PI of this proposal as well as the broader academic research community, by placing the ability to configure and acquire multimodal image data in the hands of the investigators themselves. In tandem with ongoing ARO, ARL, and DoD projects at Rutgers University, MANTIS will accelerate progress and breakthroughs in areas of major importance to the ArmyÕs ISTAR and soldier health programs. This abstract is publicly releasable

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 11, 2018
Source ID
W911NF1610209

Entities

People

  • Waheed U. Bajwa

Organizations

  • Army Contracting Command
  • Rutgers University
  • United States Army

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • Autonomy