Human Remote Sensing - Human Spectral Imaging - Remote Biometrics

 

Thermal Sensing with Long-Wave Infrared (LWIR) 

 

Figure 1: Thermal sensing/imaging with LWIR. Image produced with a Specim LWIR hyperspectral imager. (From Wikipedia - CC BY-SA 3.0, https://en.wikipedia.org/w/index.php?curid=31860190)

 

 

 

Figure 2: Thermal sensing/imaging with LWIR and pseudocolorization. From Wikipedia - by NASA/IPAC.

 

 

 

Thermal Sensing with Long-Wave Infrared - Remote Thermal Fingerprint based on skin emissivities

 

 

Figure 3: Thermal sensing/imaging with LWIR (8-14 μm) - Evaluation of "Human Thermal Fingerprint at Long Distance" by the military (From "Wired" archives - slide 13).

 

 

 

Thermal facial recognition using skin vasculature thermal imprint

 

Use of blood vessels/capillaries located just under the skin of the face
Possibility to be performed in the dark and below cover (e.g. mask)

 

Link: https://www.healthline.com/health-news/tech-thermal-face-scanning-newest-way-to-identify-at-a-distance-071713

 

 

Thermal imaging as a biometric approach

 

 
Pedestrian Detection
Face Segmentation, Ear Detection, Eye Detection
Hand Geometry Feature Extraction
Fingerprint recognition

 

 

Detection of vocalization over long distances or through barriers using Doppler radar with deep convolutional neural networks.

https://innovate.ieee.org/innovation-spotlight/doppler-radar-search-and-rescue/

 

 

 

Infrared depth detection: face recognition, motion detection, heart rate detection

 

Infrared depth detection technology, which can be considered as infrared LiDAR, consists of an infrared emitter which projects a grid of infrared dots on a scene/face and an infrared sensor which calculates distance/depth. It was originally used for motion detection for the game console Kinnect Xbox by Microsoft/PrimeSense. Kinnect 2.0 could perform face recognition and heart rate measurement. In 2017, Apple incorporated infrared depth detection technology in its iPhone X camera with the purpose of advanced face recognition. It consists of 30.000 infrared dots directed towards the subject's face to create a 3D full animated mesh.

 

https://www.theverge.com/circuitbreaker/2017/9/17/16315510/iphone-x-notch-kinect-apple-primesense-microsoft

 

 

 

 

Remote respiratory monitoring with thermal imaging

 

Nostrils have different temperatures on inhalation and exhalation. By monitoring their temperature one can determine the frequency of inhalation and exhalation and thereby the respiratory rate.

 

 

 

 

Sensing of Human Gait (cf. walking) with Doppler RADAR

 

 

Figure 4:  "The Spectrogram and Cadence Frequency of a Walking Human" pdf - p.20

 

 

 

 

Figure 5: Doppler RADAR-measured gait. From “Radar Technology For Acquiring Biological Signals” - G. Greneker (http://truth.charleshontsphd.com/JCAAWP/2006_No_2/2006_127-134.pdf)

 

 

 

Detection et localisation de cibles derrière un mur avec un système radar ULB (Thèse)

 

 

 

 

 

 

Micro-Doppler Radar Signatures for Intelligent Target Recognition

 

#AutomaticTargetRecognition #AutomaticGaitRecognition

 

Defence R&D Canada http://www.dtic.mil/dtic/tr/fulltext/u2/a427483.pdf (p15-16)

 

When the radar transmits an electromagnetic signal to a target, the signal interacts with the target and then returns to the radar. The change in the properties of the returned signal reflects on the characteristics of the target.

 

When the target is moving, the carrier frequency of the returned signal will be shifted due to Doppler effect. The Doppler frequency shift can be used to determine the radial velocity of the moving target. If the target or any structure on the target is vibrating or rotating in addition to target translation, it will induce frequency modulation on the returned signal that generates sidebands about the target's Doppler frequency. This modulation is called the microDoppler (m-D) phenomenon.

 

The m-D phenomenon can be regarded as a characteristic of the interaction between the vibrating or rotating structures and the target body. If the target undergoes a vibration or rotation, then the Doppler frequency shift generated by the vibration or rotation is a time-varying function and imposes aperiodic time-varying modulation onto the carrier frequency.

 

The modulation contains harmonic frequencies that depend on the carrier frequency, the vibration or rotation rate, and the angle between the direction of vibration and the direction of the incidentwave. While the Doppler frequency induced by the target body is constant, the m-D due to a vibrating or rotating structure of the target is a function of dwell time.

 

The micro-Doppler effect was originally introduced in laser systems, but it can also be observed in microwave radar systems. The fundamental research of the m-D phenomenon in radar is a relatively unexplored and untested area [5]. Micro-Doppler radar signatures of battlefield engine are caused by vibration. In many cases, a target or any structure on the target may have vibrations or rotations that are referred to as micro-motion dynamics. For example, vibrations generated by a vehicle engine may be detected from the surface vibration of the vehicle.

 

From the m-D signature of engine vibration signals, one can further distinguish a gas turbine engine of a tank from a diesel engine of a bus. Vehicles produce their own types of m-D signature as do helicopters. Therefore, the m-D effect can be used to identify specific types of battlefield targets and determine their movement and engine speed.

 

(…)

 

Obtaining radar signatures of personnel is another important application of m-D. The human walking gait is a complex motion behaviour that comprises different movements of individual body parts. Since September 11, Automatic Gait Recognition (AGR) technology is growing in significance. Because gait recognition technology is so new, researchers are assessing its uniqueness and methods by which it can be evaluated. Various computer vision and ultrasound techniques have been developed to measure gait parameters [26-29]. Real-Time AGR radar systems have recently been recognized as advantageous solutions for detecting, classifying and identifying human targets at distances in all light and weather conditions. Radar has certain advantages over electrooptical (EO) systems and video cameras in that it can penetrate into clothes, does not require light, and operates in fog and other low-visibility weather conditions. However, radar-based recognition is such a novel approach that much fundamental research has yet to be done in this area. The radar sends out a signal and then measures the echo that contains rich information about the various parts of the moving body.

 

There are different shifts for different body parts, because they are moving at different velocities. For example, a walking man with swinging arms may induce frequency modulation of the returned signal and generate sidebands about the body Doppler.

 

 

Classification of micro-Doppler signatures of human motions using log-Gabor filters

http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7348901

 

 

 

 

 

 

 

"Parabon® Snapshot™ is the world’s first software application that can predict appearance and ancestry from a (forensic) DNA sample."

 

From Defense Threat Reduction Agency (DTRA)'s facebook post

 

"Our project highlighted here by Armed with Science - DoD sounds like a TV crime drama but its actually being developed to help military dismantle #IED in the field. U.S. Department of Defense (DoD) #MakingTheWorldSafer

 

http://science.dodlive.mil/2017/05/22/dtra-technology-uses-dna-to-predict-what-a-person-looks-like/

 

 

 

Chaos Computer Club hackt Iriserkennung des Samsung Galaxy S8

http://www.ccc.de/de/updates/2017/iriden