Event cameras, inspired by biological vision, offer high dynamic range, excellent temporal resolution, and minimal data redundancy. Precise calibration of event camera systems is essential for applications such as 3D vision. The cessation of extra gray frame production in popular models like the dynamic vision sensor (DVS) poses significant challenges to achieving high-accuracy calibration. Traditional calibration methods, which rely on motion to trigger events, are prone to movement-related errors. This paper introduces a motion-error-free calibration method for event cameras using a flashing target produced by a standard electronic display that elicits high-fidelity events. We propose an improved events-accumulator to reconstruct gray images with distinct calibration features and develop an optimization method that adjusts camera parameters and control point positions simultaneously, enhancing the calibration accuracy of event camera systems. Experimental results demonstrated higher accuracy compared to the traditional motion-based calibration method (reprojection error: 0.03 vs. 0.96 pixels). The 3D reconstruction error remained around 0.15 mm, significantly improving over the motion-based method's 8.00 mm. Additionally, the method's adaptability for hybrid calibration in event-based stereovision systems was verified (e.g., with frame cameras or projectors).
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Sci Rep
January 2025
Department of Information Technology Management, Faculty of Management Technology and Information System, Port Said University, Port Said, 42526, Egypt.
The Internet of Things (IoTs) has revolutionized cities, enabling them to become smarter. IoTs play an important role in monitoring the traffic cameras, roads, smart farming, connected vehicles, air quality, water level, humidity, and carbon dioxide pollution levels in city buildings. One of the major challenges of smart cities is the cyber threat to sensitive data.
View Article and Find Full Text PDFAm J Biol Anthropol
January 2025
Primate Models for Behavioural Evolution Lab, Institute of Human Sciences, University of Oxford, Oxford, UK.
Objectives: With contemporary, human-induced climate change at a crisis point, extreme weather events (e.g., cyclones, heatwaves, floods) are becoming more frequent, intense, and difficult to predict.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Technische Hochschule Nürnberg Georg Simon Ohm, Institute of Hydraulic Engineering and Water Resources Management, Nuremberg, Germany.
Through the mobilization of movable objects due to the extreme hydraulic conditions during a flood event, blockages, damage to infrastructure, and endangerment of human lives can occur. To identify potential hazards from aerial imagery and take appropriate precautions, a change detection tool (CDT) was developed and tested using a study area along the Aisch River in Germany. The focus of the CDT development was on near real-time analysis of point cloud data generated by structure from motion from aerial images of temporally separated surveys, enabling rapid and targeted implementation of measures.
View Article and Find Full Text PDFSci Rep
December 2024
Graduate School of Engineering, University of Miyazaki, Miyazaki, 889-2192, Japan.
Accurate calving time prediction plays a critical role in ensuring the well-being of both mother and calf during parturition. Challenges during the calving process, particularly in abnormal cases, often necessitate human intervention to prevent potentially fatal outcomes. This study proposes a novel system for automated prediction of normal and abnormal cattle calving cases based on posture analysis.
View Article and Find Full Text PDFNat Commun
December 2024
State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China.
Imaging flow cytometry allows image-activated cell sorting (IACS) with enhanced feature dimensions in cellular morphology, structure, and composition. However, existing IACS frameworks suffer from the challenges of 3D information loss and processing latency dilemma in real-time sorting operation. Herein, we establish a neuromorphic-enabled video-activated cell sorter (NEVACS) framework, designed to achieve high-dimensional spatiotemporal characterization content alongside high-throughput sorting of particles in wide field of view.
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