3-D Object Tracking in Panoramic Video and LiDAR for Radiological Source–Object Attribution and Improved Source Detection

Abstract

Networked detector systems can be deployed in urban environments to aid in the detection and localization of radiological and/or nuclear material. However, effectively responding to and interpreting a radiological alarm using spectroscopic data alone may be hampered by a lack of situational awareness, particularly in complex environments. This study investigates the use of LiDAR and streaming video to enable real-time object detection and tracking, and the fusion of this tracking information with radiological data for the purposes of enhanced situational awareness and increased detection sensitivity. This work presents a novel object detection, tracking, and source-object attribution analysis that is capable of operating in real-time. By implementing this analysis pipeline on a custom developed system that comprises a static 2 × 4 × 16 inch NaI(Tl) detector co-located with a 64-beam LiDAR and 4 monocular cameras, we demonstrate the ability to accurately correlate trajectories from tracked objects to spectroscopic gamma-ray data in real time, and use physics-based models to reliably discriminate between source-carrying and non-source-carrying objects. In this work, we describe our approach in detail and present a quantitative performance assessment that characterizes the source-object attribution capabilities of both video and Li-DAR. Additionally, we demonstrate the ability to simultaneously track pedestrians and vehicles in a mock urban environment, and use this tracking information to improve both detection sensitivity and situational awareness using our contextual-radiological data fusion methodology.

Free-moving Quantitative Gamma-ray Imaging

“…Mapping can and has been demonstrated with both structured light 15 , 17 and lidar sensors 18 , 19 . Similar work has also been demonstrated, including lidar-based SLAM with a mobile ground-robot 22 , offline photogrammetry (in place of SLAM) for ground-based 23 and airborne systems 24 , as well as object detection, tracking and source attribution in visual and lidar data for static systems 25 , 26 .…”

Research on Wushu Sports Feedback System Based on Real-Time Target Intelligent Tracking Video Processing

“…It is not only a data source for intelligent target tracking attitude reconstruction based on video, but also a data source for intelligent target tracking attitude reconstruction based on video. Furthermore, according to the motion database, the spatiotemporal models (spatial structure similarity model and Markov time probability transfer model) provide important guiding information for human motion reconstruction, which is an important basis for automatic continuous motion generation in this paper [20]. erefore, how to establish such a target intelligent tracking human motion database is very important [21].…”

Abnormal Frame Extraction and Object Tracking Hybrid Machine Learning

“…16 in. NaI(Tl) detector, 64beam LiDAR, and four monocular cameras, to enhance detection and situational awareness while This existing research keeps an eye on pedestrians and vehicles in a simulated city environment [9]. This existing research presents a deep neural networkbased method for identifying objects in videos for subsequent retargeting.…”