Featured Research

3D Augmented Reality Devices

Seeing through obscurations and automated object recognition with 3D augmented reality devices.

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  1. 2D imaging cannot see through obscurations
  2. 3D reconstructed image can see through partial obscurations
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 The 3D object visualized by the viewer with removed obscurations using an augmented reality device.
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 Typical augmented reality device in the experiments
For more details, see Adam Markman, Xin Shen, Hong Hua, and Bahram Javidi, “Augmented reality three-dimensional object visualization and recognition with axially distributed sensing,” Optics Letters 41, issue 2, pp 297-300 (January 2016)

3D Human Gesture and Activity Recognition
3-D Gesture Recognition Experiments

Images show the reconstruction capability of the system, for the same frame, and for a specific person and gesture:

  1. background,
  2. head, and
  3. fist
  4. Depth reconstruction focusing at the hand’s gesture open,
  5. Depth reconstruction focusing at the hand’s gesture left, and
  6. Depth reconstruction focusing at the hand’s gesture deny.

For details, see V. Javier Traver, Pedro Latorre-Carmona, Eva Salvador-Balaguer, Filiberto Pla, and Bahram Javidi, “Human gesture recognition using three-dimensional integral imaging,” The Journal of the Optical Society of America A, vol. 31, pp 2312-2320 (2014)

3D Displays
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Concept of 3D Displays using Integral Imaging

  1. Image capture stage
  2. 3D Display stage, which produces floating 3-D images in front of the monitor
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c. Two views of the 3-D image as displayed by the Integral Imaging 3D display

Source: Manuel Martínez-Corral, Adrián Dorado, Juan Carlos Barreiro, Genaro Saavedra, and Bahram Javidi, “Recent Advances in the Capture and Display of Macroscopic and Microscopic 3-D Scenes by Integral Imaging,” the Proceedings of IEEE Journal, Volume 105, Issue 5, 2017.

3D Object Tracking from behind Obscurations

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  1. scene capture process and
  2. 3D reconstruction of the scene
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 3. Segmented and tracked objects from behind occlusion

Long Range 3D Imaging for Defense and Security Applications

a. Tests conducted from the US Air Force Sensors Directorate tower and camera railb. Results of the obscuration penetration experiment

Source: Daniel LeMaster, Barry Karch, and Bahram Javidi, “Mid-Wave Infrared 3D Integral Imaging at Long Range,” IEEE Journal of Display Technology, vol. 9, pp. 545-551 (1 July 2013)

Multidimensional Optical Sensing and Imaging System (MOSIS)

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MOSIS 2.0 for 3-D object shape and material inspection experiments in the presence of occlusion. Captured and computed multidimensional elemental images.

  1. Visible spectrum and
  2. NIR spectrum.
  3. Degree of polarization (DoP) computed by the Stokes parameters and
  4. depth map by the estimation method

Source: Bahram Javidi, Xin Shen, Adam S. Markman, Pedro Latorre-Carmona, Adolfo Martínez-Uso, José Martinez Sotoca, Filiberto Pla, Manuel Martínez-Corral, Genaro Saavedra, Yi-Pai Huang, Adrian Stern, “Multidimensional Optical Sensing and Imaging Systems (MOSIS): From Macro to Micro Scales,” the Proceedings of the IEEE Journal, Volume 105, Issue 5, 2017
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Diagram of the Multidimensional Optical Sensing and Imaging System (MOSIS)

Hardware Security and Authentication of Integrated Circuits using Micro/Nano Optical ID Tags
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(a) 449×641 pixel binary image.

(b) 3.15 mm x 3.15 mm QR code storing the encrypted and compressed image shown in (a) placed on a 14.5 mm x 52.1 mm IC; an image of the QR code placed next to a dime is also depicted
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Enlarged QR code taken using the iPhone 4 camera; and scanned QR code depicting the encrypted and compressed data using the iPhone SCAN Application

Source: A. Markman, B. Javidi, and M. Tehranipoor, “Photon-Counting Security Tagging and Verification Using Optically Encoded QR Codes,” (IEEE) Photonics Journal, vol. 6, issue 1, 2014

Bio Photonics, 3D Microscopy, and Automated Disease Identification
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 Schematics of an experimental setup to measure the complex amplitude of red blood cells (RBCs) to capture opto-biological signatures
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(a), (d) Shearing interferograms.

(b), (e) RBC gradient phase image retrieved from shearing interferograms in (a) and (d), respectively.

(c), (f) RBC gradient amplitude image retrieved from shearing interferograms in (a) and (d) respectively.

(a)–(c) Are from a healthy RBC, whereas (d)–(f) are from a malaria infected RBC

Source: I. Moon, A. Anand, M. Cruz, and B. Javidi, “Identification of Malaria Infected Red Blood Cells via Digital Shearing Interferometry and Statistical Inference, ”IEEE Photonics Journal, Volume 5, Number 5, October 2013

Security, Anti-Counterfeiting, and Authentication using Nano Technologies
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  1. AuNP (gold) QR code (sample A),
  2. platinum QR code (sample B), and
  3. AuNP (gold) structure without QR code (sample C)
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 Optical setup for authentication of codes produced with gold nanoparticles
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Principal component analysis of the histograms. Red dots, sample A; green dots, sample B; blue dots, sample C

Sources: A. Carnicer, A. Hassanfiroozi, P. Latorre-Carmona, Y.-P. Huang, and B. Javidi, “Security authentication using phase-encoded nanoparticle structures and polarized light,” Opt. Lett. 40, 135–138 (2015); and Artur Carnicer and Bahram Javidi, “Optical Security and Authentication using Nanoscale and Thin Film structures,” Advances in Optics and Photonics, vol 9, issue 2, pp 218-256, June 30, 2017

Underwater Sensing Consisting of Underwater Vehicles (AUV)
Figure (a) An example of underwater sensing consisting of underwater vehicles (AUV) communicating with each other. (b) Integral Imaging sensing. (c) Diagram of integral imaging experimental setup to capture video sequences of the optical signal sent by the light source (blue LED).
Source: S. Komatsu, A. Markman, and B. Javidi, “Optical sensing in turbid water using multi-dimensional integral imaging,” Optics Letters, 43(14), 3261-3264 (2018).