Correction to: A Robotic Augmented Reality Virtual Window for Law Enforcement Operations

We report on an experiment on the distracting effects of in-car conversations through augmented-reality glasses. Previous research showed that in-car phone conversations can be distracting, but that the distraction might be reduced if the remote caller receives visual information about the driving context. However, what happens if such video sharing becomes bidirectional? The recent introduction of commercial augmented-reality glasses in particular might allow drivers to engage in video-supported conversations while driving. We investigate how distracting such video-based conversations are in an experiment. Our participants operated a simulated vehicle, while also playing a conversational game (Taboo) with a remote conversant. The driver either only heard the remote conversant (speech-only condition), or was also able to see the remote person in a virtual window that was presented through augmented reality (video call condition). Results show that our participants did not spend time looking at the video of the remote conversant. We hypothesize that this was due to the fact that in our experiment participants had to turn their head to get a full view of the virtual window. Our results imply that we need further studies on the effects of augmented reality on the visual attention of the driver, before the technology is used on the road.

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Improving the View of the World: Law Enforcement and Augmented Reality Technology

PsycEXTRA Dataset ◽

10.1037/e313222004-004 ◽

2004 ◽

Cited By ~ 2

Author(s):

Thomas Cowper

Keyword(s):

Law Enforcement ◽

Augmented Reality ◽

The World ◽

Augmented Reality Technology

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DARLENE – Improving situational awareness of European law enforcement agents through a combination of augmented reality and artificial intelligence solutions

Open Research Europe ◽

10.12688/openreseurope.13715.1 ◽

2021 ◽

Vol 1 ◽

pp. 87

Author(s):

Konstantinos C. Apostolakis ◽

Nikolaos Dimitriou ◽

George Margetis ◽

Stavroula Ntoa ◽

Dimitrios Tzovaras ◽

...

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Computer Vision ◽

Law Enforcement ◽

Augmented Reality ◽

Pose Estimation ◽

Situational Awareness ◽

Estimation Method ◽

Violence Detection ◽

Wide Range

Background: Augmented reality (AR) and artificial intelligence (AI) are highly disruptive technologies that have revolutionised practices in a wide range of domains. Their potential has not gone unnoticed in the security sector with several law enforcement agencies (LEAs) employing AI applications in their daily operations for forensics and surveillance. In this paper, we present the DARLENE ecosystem, which aims to bridge existing gaps in applying AR and AI technologies for rapid tactical decision-making in situ with minimal error margin, thus enhancing LEAs’ efficiency and Situational Awareness (SA). Methods: DARLENE incorporates novel AI techniques for computer vision tasks such as activity recognition and pose estimation, while also building an AR framework for visualization of the inferenced results via dynamic content adaptation according to each individual officer’s stress level and current context. The concept has been validated with end-users through co-creation workshops, while the decision-making mechanism for enhancing LEAs’ SA has been assessed with experts. Regarding computer vision components, preliminary tests of the instance segmentation method for humans’ and objects’ detection have been conducted on a subset of videos from the RWF-2000 dataset for violence detection, which have also been used to test a human pose estimation method that has so far exhibited impressive results and will constitute the basis of further developments in DARLENE. Results: Evaluation results highlight that target users are positive towards the adoption of the proposed solution in field operations, and that the SA decision-making mechanism produces highly acceptable outcomes. Evaluation of the computer vision components yielded promising results and identified opportunities for improvement. Conclusions: This work provides the context of the DARLENE ecosystem and presents the DARLENE architecture, analyses its individual technologies, and demonstrates preliminary results, which are positive both in terms of technological achievements and user acceptance of the proposed solution.

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Pyrotechnic Residues in Gunshot Residue Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100117649 ◽

1985 ◽

Vol 43 ◽

pp. 128-129

Author(s):

H. M. Sagara ◽

S. A. Schliebe ◽

M. C. Kong

Keyword(s):

Law Enforcement ◽

Residue Analysis ◽

Gunshot Residue ◽

Particle Analysis ◽

Dry Skin ◽

X Ray ◽

Skin Cells ◽

Smokeless Powder ◽

Carbon Coated ◽

Detailed List

Particle analysis by scanning electron microscopy with energy-dispersive x- ray analysis is one of the current methods used in crime laboratories to aid law enforcement in identifying individuals who have recently fired or handled a firearm. During the discharge of a firearm, the high pressure caused by the detonation of the cartridge materials forces a portion of the generated gases through leaks in the firing mechanism of the weapon. These gases contain residues of smokeless powder, primer mixture, and contributions from the projectile itself. The condensation of these hot gases form discrete, micrometer-sized particles, which can be collected, along with dry skin cells, salts, and other hand debris, from the hands of a shooter by a simple adhesive lift technique. The examination of the carbon-coated adhesive lifts consist of time consuming systematic searches for high contrast particles of spherical morphology with the characteristic elemental composition of antimony, barium and lead. A detailed list of the elemental compositions which match the criteria for gunshot residue are discussed in the Aerospace report.

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