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4th IEEE Global Conference for Advancement in Technology, GCAT 2023

作者： Peri, Sai Deepa Bhavani Palaniswamy, Suja Department of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350305258

This paper introduces a novel approach for the segmentation, detection, and tracking small animals and insects like butterflies and squirrels using the YOLOv8 object detection model and Deep SORT tracking algorithm. With a high recall score of 0.9, the proposed methodology enables accurate detection and tracking of these creatures. tracking small insects and animals like butterflies and squirrels is crucial for understanding their ecology and implementing effective conservation strategies. The results demonstrate its ability to accurately track these creatures across diverse settings, including varying lighting conditions and backgrounds. The proposed methodology approach offers several advantages over existing methods. It enables tracking of both air and land-based creatures, surpasses the accuracy of hand-crafted feature-based approaches. The findings highlight the potential of our approach for butterfly and squirrel tracking, advancing ecological studies and contributing to species preservation. The Big Butterfly Count serves as a valuable resource for tracking butterflies and supporting their conservation efforts. © 2023 IEEE.

关键词： animal behavior butterfly tracking conservation Deep SORT ecological research object detection squirrel tracking tracking algorithms Wildlife tracking YOLOv8

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Evaluation of Horizontal Single-Axis Solar Tracker algorithms in Terms of Energy Production and Operational Performance

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SOLAR RRL 2024年第1期8卷

作者： Munoz, Ildefonso Guinda, Adrian Olivares, Gregorio Diaz, Sara Gracia-Amillo, Ana M. Casajus, Luis CENER Natl Renewable Energy Ctr Spain Dept Solar Energy Technol & Storage C Ciudad Innovac 7 Sarriguren 31621 Spain

Horizontal single-axis solar tracking systems with Astronomical tracking algorithm are commonly used in photovoltaic (PV) installations. However, different algorithms can increase the PV installation's performance without implementing new equipment or technologies. In this article, the performance of three tracking algorithms is compared to the Astronomical one. Two algorithms aim at optimizing the received irradiance focusing on the diffuse component. The third one, called Analytical, is presented as a new development in this study, defining the optimal inclination angle depending on all radiation components. The comparison focuses on different parameters like the in-plane irradiance, DC power output from a monofacial PV system and operational aspects like the performed number of movements. High-time-resolution (1 min) simulations are performed with proprietary software taking into account several effects on the effective irradiance and power output estimation, such as shading effects or PV configuration. Eight locations with different climatic conditions are analyzed. All three algorithms derive in higher in-plane irradiance and power output values than the Astronomical algorithm, although the gain depends on the climatic conditions. At locations with high diffuse fraction, the power output from the Analytical algorithm, which outperforms the others, can be up to 3% higher than the Astronomical one. Four tracking algorithms for one-horizontal-axis tracking system are studied under different climatic conditions. The in-plane irradiance, power output of a monofacial photovoltaic system, and the number of movements performed following the different algorithms are analysed. Differences between algorithms and climatic conditions are significant, especially under predominant cloudy conditions where 3% energy output gain is *** (c) 2023 WILEY-VCH GmbH

关键词： high resolutions photovoltaic (PV) performances solar trackers tracking algorithms

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Application of Radar Solutions for the Purpose of Bird tracking Systems Based on Video Observation

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SENSORS 2022年第10期22卷 3660-3660页

作者： Krenc, Ksawery Gradolewski, Dawid Dziak, Damian Kawalec, Adam Bioseco SA Budowlanych 68 PL-80298 Gdansk Poland Mil Univ Technol Fac Mechatron Armament & Aerosp Sylwestra Kaliskiego 2 PL-00908 Warsaw Poland

Wildlife Hazard Management is nowadays a very serious problem, mostly at airports and wind farms. If ignored, it may lead to repercussions in human safety, ecology, and economics. One of the approaches that is widely implemented in small and medium-size airports, as well as on wind turbines is based on a stereo-vision. However, to provide long-term observations allowing the determination of the hot spots of birds' activity and forecast future events, a robust tracking algorithm is required. The aim of this paper is to review tracking algorithms widely used in Radar Science and assess the possibilities of application of these algorithms for the purpose of tracking birds with a stereo-vision system. We performed a survey-of-related works and simulations determined five state-of-the art algorithms: Kalman Filter, Nearest-Neighbour, Joint-Probabilistic Data Association, and Interacting Multiple Model with the potential for implementation in a stereo-vision system. These algorithms have been implemented and simulated in the proposed case study

关键词： bird tracking tracking algorithms camera detection visual sensor network wildlife hazard management stereo-vision

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Statistical analysis of long-lived mesoscale eddies in the Lofoten basin from satellite altimetry

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ADVANCES IN SPACE RESEARCH 2021年第2期68卷 364-377页

作者： Gordeeva, Svetlana Zinchenko, Vadim Koldunov, Aleksey Raj, Roshin P. Belonenko, Tatyana St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia Russian State Hydrometeorol Univ 79 Voronezhskaya Ul St Petersburg 192007 Russia Russian Acad Sci Shirshov Inst Oceanol 36 Nahimovskiy Pr Moscow 117997 Russia Bjerknes Ctr Climate Res Nansen Environm & Remote Sensing Ctr Thormohlens Gate 47 N-5006 Bergen Norway

The paper presents a statistical analysis of long-lived detected mesoscale eddies in the Lofoten Basin (LB). An automated eddy iden-tification and tracking method is applied to the altimeter data during the time-period 1993-2017 to detect and track anticyclonic (ACEs) and cyclonic eddies (CEs) in the LB. Our analysis found that only one percent of the eddies detected are long-lived (eddy-life > 35 days). Even though only 1%, the detected 330 long-lived mesoscale eddies (CEs, 120;ACEs, 210) account for >11,550 daily individual eddy-observations. The lifetime, occurrence, generation sites, size, intensity, and drift of these long-lived eddies are quantified. The average drift speed of long-lived eddies is found to show a pronounced seasonal variation with a maximum from October to March. Long-lived eddies in the LB are further divided into four groups based on their region of generation and dissipation. Long-lived eddies gen-erated and dissipated outside the region of the Lofoten Vortex (group 2 eddies) are found to be the predominant type (CEs, 73.3%;ACEs, 69.5%). The eddies generated and dissipated in the region of the permanent Lofoten Vortex form the second dominant type (CEs, 14.3%;ACEs, 26.2%). Based on their lifetime, properties of the two predominant groups of eddies are examined in detail. The difference found in the temporal variability of the eddy characteristics of the two groups reflects their different genesis. The analysis revealed that the mesoscale eddies of group 2 have a longer life than eddies of group 1, and ACEs are more long-lived in comparison to CEs. The analysis also found three main areas of eddy generation in the frontal zone of the NwASC from where mesoscale eddies propagate to the north-west, forming three main corridors of trajectories. The study further provides evidence of long-lived cyclonic CEs surrounding the large quasi-permanent Lofoten Vortex (LV) and forming a shield around it. Small CEs located in two areas with centers at 69.5

关键词： Lofoten basin Mesoscale eddies Altimetry Automatic detection tracking algorithms Statistical analyses

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Bayesian information fusion and multitarget tracking for maritime situational awareness

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IET RADAR SONAR AND NAVIGATION 2020年第12期14卷 1845-1857页

作者： Gaglione, Domenico Soldi, Giovanni Meyer, Florian Hlawatsch, Franz Braca, Paolo Farina, Alfonso Win, Moe Z. NATO Ctr Maritime Res & Expt CMRE La Spezia Italy Univ Calif San Diego Scripps Inst Oceanog La Jolla CA 92093 USA Univ Calif San Diego Elect & Comp Engn Dept La Jolla CA 92093 USA TU Wien Inst Telecommun Vienna Austria MIT Lab Informat & Decis Syst LIDS 77 Massachusetts Ave Cambridge MA 02139 USA

The goal of maritime situational awareness (MSA) is to provide a seamless wide-area operational picture of ship traffic in coastal areas and the oceans in real time. Radar is a central sensing modality for MSA. In particular, oceanographic high-frequency surface-wave (HFSW) radars are attractive for surveying large sea areas at over-the-horizon distances, due to their low environmental footprint and low power requirements. However, their design is not optimal for the challenging conditions prevalent in MSA applications, thus calling for the development of dedicated information fusion and multisensor-multitarget tracking algorithms. In this study, the authors show how the multisensor-multitarget tracking problem can be formulated in a Bayesian framework and efficiently solved by running the loopy sum-product algorithm on a suitably devised factor graph. Compared to previously proposed methods, this approach is advantageous in terms of estimation accuracy, computational complexity, implementation flexibility, and scalability. Moreover, its performance can be further enhanced by estimating unknown model parameters in an online fashion and by fusing automatic identification system (AIS) data and context-based information. The effectiveness of the proposed Bayesian multisensor-multitarget tracking and information fusion algorithms is demonstrated through experimental results based on simulated data as well as real HFSW radar data and real AIS data.

关键词： target tracking ships oceanographic techniques sensor fusion radar detection Bayes methods radar tracking geophysical signal processing marine radar Bayesian information fusion maritime situational awareness wide-area operational picture ship traffic coastal areas central sensing modality high-frequency surface-wave radars sea areas over-the-horizon distances low environmental footprint low power requirements MSA applications dedicated information fusion tracking algorithms multisensor-multitarget tracking problem Bayesian framework loopy sum-product algorithm suitably devised factor graph authors context-based information information fusion algorithms HFSW radar data

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A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video tracking

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SENSORS 2021年第15期21卷 5117-5117页

作者： Perpetuini, David Cardone, Daniela Filippini, Chiara Chiarelli, Antonio Maria Merla, Arcangelo Univ G dAnnunzio Inst Adv Biomed Technol Dept Neurosci Imaging & Clin Sci Via Luigi Polacchi 13 I-66100 Chieti Italy

Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes' movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes' movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes' movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.

关键词： motion artefacts functional near infrared spectroscopy (fNIRS) infrared imaging infrared thermography wavelet transform wavelet coherence tracking algorithms

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Artificial intelligence-assisted ultrasound-guided regional anaesthesia: An explorative scoping review

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JOURNAL OF EXPERIMENTAL ORTHOPAEDICS 2024年第3期11卷 e12104页

作者： Marino, Martina Hagh, Rebecca Senorski, Eric Hamrin Longo, Umile Giuseppe Oeding, Jacob F. Nellgard, Bengt Szell, Anita Samuelsson, Kristian Fdn Policlin Univ Campus Biomed Via Alvaro del Portillo Rome Italy Univ Campus Biomed Roma Dept Med & Surg Res Unit Orthopaed & Trauma Surg Via Alvaro del Portillo I-00128 Rome Italy Sahlgrenska Sports Med Ctr Gothenburg Sweden Univ Gothenburg Sahlgrenska Acad Inst Neurosci & Physiol Dept Hlth & Rehabil Gothenburg Sweden Univ Gothenburg Sahlgrenska Acad Inst Clin Sci Dept Orthopaed Gothenburg Sweden Mayo Clin Sch Med Alix Sch Med Rochester MN USA Univ Gothenburg Sahlgrenska Acad Inst Clin Sci Dept Anesthesiol & Intens Care Gothenburg Sweden

Purpose: The present study reviews the available scientific literature on artificial intelligence (AI)-assisted ultrasound-guided regional anaesthesia (UGRA) and evaluates the reported intraprocedural parameters and postprocedural outcomes. Methods: A literature search was performed on 19 September 2023, using the Medline, EMBASE, CINAHL, Cochrane Library and Google Scholar databases by experts in electronic searching. All study designs were considered with no restrictions regarding patient characteristics or cohort size. Outcomes assessed included the accuracy of AI-model tracking, success at the first attempt, differences in outcomes between AI-assisted and unassisted UGRA, operator feedback and case-report data. Results: A joint adaptive median binary pattern (JAMBP) has been applied to improve the tracking procedure, while a particle filter (PF) is involved in feature extraction. JAMBP combined with PF was most accurate on all images for landmark identification, with accuracy scores of 0.83, 0.93 and 0.93 on original, preprocessed and filtered images, respectively. Evaluation of first-attempt success of spinal needle insertion revealed first-attempt success in most patients. When comparing AI application versus UGRA alone, a significant statistical difference (p < 0.05) was found for correct block view, correct structure identification and decrease in mean injection time, needle track adjustments and bone encounters in favour of having AI assistance. Assessment of operator feedback revealed that expert and nonexpert operator feedback was overall positive. Conclusion: AI appears promising to enhance UGRA as well as to positively influence operator training. AI application of UGRA may improve the identification of anatomical structures and provide guidance for needle placement, reducing the risk of complications and improving patient outcomes. Level of EvidenceLevel IV.

关键词： convolutional neural networks landmark identification machine learning algorithms tracking algorithms

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Animal tracking Method Used in Neuroscience Experiments 8

Animal Tracking Method Used in Neuroscience Experiments

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8th International Conference on E-Health and Bioengineering (EHB)

作者： Rotaru, Florin Bejinariu, Silviu-Ioan Costin, Hariton Luca, Ramona Nita, Cristina Diana Romanian Acad Inst Comp Sci Iasi Branch Iasi Romania Gr T Popa Univ Med & Pharm Fac Med Bioengn Iasi Romania

ISBN: (纸本)9781728188034

In neuroscience research, laboratory animals and especially monkeys are often used in experiments. Besides the neural signals provided by radio from a sensor array mounted on the monkey head, also the head position and orientation are needed for a complete analysis. In this paper, a monkey tracking and head orientation computation method is proposed. The procedure was validated using a database of four videos, visualizing experiments of a total duration of 3 hours and 48 minutes.

关键词： tracking algorithms video analysis image processing

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A video-based object detection and tracking system for weight sensitive UAVs

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第7期78卷 9149-9167页

作者： Abughalieh, Karam M. Sababha, Belal H. Rawashdeh, Nathir A. Princess Sumaya Univ Technol Comp Engn Dept Amman 11941 Jordan German Jordanian Univ Dept Mechatron Engn Amman 11180 Jordan

The capability of detecting and tracking targets can play a significant role in mobile robot navigation systems. Visual tracking systems may control the direction and speed of motion of a robot to keep the target in its field of view either by moving the robot itself or the vision sensors. In this work, a compact size tracking and guiding system that could be mounted on weight-sensitive UAV platforms is presented. The system combines a motion detection technique that could be used with non-static cameras in addition to color filtering to detect and track objects in the field of view of a UAV. This hybrid system provides a reliable tracking system for low resolution images taken by a UAV camera. The proposed system implements keypoint detection algorithms including SIFT, SURF and FAST, a motion detection method using frame subtraction and object detection algorithms using color back projection in a hybrid approach that utilizes the best of each algorithm and avoids heavy usage of computing resources. Keypoint detectors SURF, SIFT and FAST are tested and implemented for the purpose of image alignment and frame subtractions. Experimental tests showed the system's ability to detect and track low detailed targets. The system is tested on a UAV using a Raspberry Pi 2 mini-computer running OpenCV libraries and was able to process eleven frames per second implementing object detection and tracking. The test objects were mainly cars monitored from different altitudes through a UAV downward pointing camera.

关键词： Computer vision Object tracking tracking algorithms Aerial video processing Keypoint detector Background subtraction UAV OpenCV

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Track finding at Belle II

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COMPUTER PHYSICS COMMUNICATIONS 2021年 259卷 107610-107610页

作者： Bertacchi, Valerio Bilka, Tadeas Braun, Nils Casarosa, Giulia Corona, Luigi Cunliffe, Sam Dattola, Filippo De Marino, Gaetano De Nuccio, Michael De Pietro, Giacomo Thanh Van Dong Dujany, Giulio Ecker, Patrick Eliachevitch, Michael Fillinger, Tristan Frost, Oliver Fruehwirth, Rudolf Gebauer, Uwe Glazov, Sasha Gosling, Nicolas Guo, Aiqiang Hauth, Thomas Heck, Martin Kaleta, Mateusz Kandra, Jakub Kleinwort, Claus Kuhr, Thomas Kurz, Simon Kvasnicka, Peter Lettenbichler, Jakob Lueck, Thomas Martini, Alberto Metzner, Felix Neverov, Dmitrii Niebuhr, Carsten Paoloni, Eugenio Patra, Sourav Piilonen, Leo Praz, Cyrille Prim, Markus Tobias Pulvermacher, Christian Racs, Sebastian Rad, Navid Rados, Petar Ritter, Martin Rizzo, Giuliana Rostomyan, Armine Scavino, Bianca Schlueter, Tobias Schwenker, Benjamin Spataro, Stefano Spruck, Bjorn Svidras, Henrikas Tenchini, Francesco Uematsu, Yuma Webb, James Wessel, Christian Zani, Laura Scuola Normale Super Pisa Largo B Pontecorvo 3 I-56127 Pisa Italy INFN Sez Pisa Largo B Pontecorvo 3 I-56127 Pisa Italy Charles Univ Prague Inst Particle & Nucl Phys Ke Karlovu 3 Prague 12116 Czech Republic Karlsruhe Inst Technol KIT Inst Expt Particle Phys ETP Wolfgang Gaede Str 1 D-76131 Karlsruhe Germany Univ Pisa Dipartimento Fis Largo B Pontecorvo 3 I-56127 Pisa Italy Deutsch Elektronen Synchrotron DESY Notkestr 85 D-22607 Hamburg Germany Lab Laccelerateur Lineaire LAL Orsay Batiment 200BP34 F-91898 Orsay France Univ Roma Tre Dipartimento Matemat & Fis Via Vasca Navale 84 I-00146 Rome Italy INFN Sez Roma Tre Via Vasca Navale 84 I-00146 Rome Italy Fudan Univ Key Lab Nucl Phys & Ion Beam Applicat MOE Shanghai 200443 Peoples R China Inst Modern Phys Shanghai 200443 Peoples R China Univ Strasbourg CNRS IPHC UMR 7178 F-67037 Strasbourg France Rheinische Friedrich Wilhelms Univ Phys Inst Nussallee 12 D-53115 Bonn Germany Austrian Acad Sci Inst High Energy Phys Nikolsdorfer Gasse 18 A-1050 Vienna Austria Univ Gottingen Fac Phys Friedrich Hund Pl 1 D-37077 Gottingen Germany Ludwig Maximilians Univ Munchen LMU Fac Phys Geschwister Scholl Pl 1 D-80539 Munich Germany Inst High Energy Phys IHEP 19B Yuquan Rd Beijing Peoples R China Inst Nucl Phys PAN Div Particle Phys & Astrophys Dept Lepton Interact Ul Radzikowskiego 152 PL-31342 Krakow Poland Nagoya Univ Grad Sch Sci Chikusa Ku Furou Cho Nagoya Aichi 4648602 Japan Indian Inst Sci Educ & Res IISER Mohali Sect 81 Manauli 140306 Punjab India Virginia Polytech Inst & State Univ 315 A Robeson Hall Blacksburg VA 24061 USA Johannes Gutenberg Univ Mainz Johann Joachim Becher Weg 45 D-55128 Mainz Germany LP Res Inc Minato City Tokyo 1060031 Japan INFN Via P Giuria 1 I-10125 Turin Italy Univ Torino Via P Giuria 1 I-10125 Turin Italy Univ Tokyo Dept Phys Grad Sch Sci Bunkyo Ku 7-3-1 Hongo Tokyo 1130033 Japan Univ Melbourne Sch Phys Melbourne Vic 3010 Australia

This paper describes the track-finding algorithm that is used for event reconstruction in the Belle II experiment operating at the SuperKEKB B-factory in Tsukuba, Japan. The algorithm is designed to balance the requirements of a high efficiency to find charged particles with a good track parameter resolution, a low rate of spurious tracks, and a reasonable demand on CPU resources. The software is implemented in a flexible, modular manner and employs a diverse selection of global and local track-finding algorithms to achieve an optimal performance. (C) 2020 Elsevier B.V. All rights reserved.

关键词： tracking algorithms Belle II tracking detectors

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