Embedded 3D reconstruction of dynamic objects in real time for maritime situational awareness pictures

Abstract

Assessing the security status of maritime infrastructures is a key factor for maritime safety and security. Facilities such as ports and harbors are highly active traffic zones with many different agents and infrastructures present, like containers, trucks or vessels. Conveying security-related information in a concise and easily understandable format can support the decision-making process of stakeholders, such as port authorities, law enforcement agencies and emergency services. In this work, we propose a novel real-time 3D reconstruction framework for enhancing maritime situational awareness pictures by joining temporal 2D video data into a single consistent display. We introduce and verify a pipeline prototype for dynamic 3D reconstruction of maritime objects using a static observer and stereoscopic cameras on an GPU-accelerated embedded device. A simulated dataset of a harbor basin was created and used for real-time processing. Usage of a simulated setup allowed verification against synthetic ground-truth data. The presented pipeline runs entirely on a remote, low-power embedded system with $$\sim $$ ∼ 6 Hz. A Nvidia Jetson Xavier AGX module was used, featuring 512 CUDA-cores, 16 GB memory and an ARMv8 64-bit octa-core CPU.

Real-time indoor tracking for augmented reality using computer vision technique

“…The indoor navigation system is built upon a combination of technologies, such as placenote Software Development Kit (SDK), the Unity3D, and cloud computing, to ensure its robust functionality and performance [26]. Xcode integrated development environment (IDE), and various computer vision algorithms such as ORB, BFM, KNN, and A* algorithms [27].…”