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作者： Bažout, David Brno University of Technology

Cílem této práce je vytvořit nástroj umožňující vyhledávání podezřelých osob ve videozáznamu pocházejícího z dohledových kamer. Hledané ... 详细信息

Cílem této práce je vytvořit nástroj umožňující vyhledávání podezřelých osob ve videozáznamu pocházejícího z dohledových kamer. Hledané osoby jsou systému určeny pomocí několika fotografií obličeje. Výstup tvoří informace o výskytu hledaných osob na konkrétních snímcích. Úloha je řešena rozdělením problému na detekci tváře a její následnou identifikaci. Experimenty s existujícími přístupy na vhodných datových sadách zajišťují relevantní porovnání úspěšnosti metod za různých podmínek. Výstupy testů umožňují vybrat vhodné metody a jejich optimální nastavení pro tuto konkrétní úlohu. Práce se zabývá i návrhem vhodné architektury, průzkumem existujících knihoven implementujících zkoumané metody a dalšími způsoby optimalizace výpočtu. Výsledkem je implementace uživatelské aplikace splňující zadané parametry. Její funkce byla otestována na vlastní datové sadě věrně napodobující podmínky reálného provozu.

关键词： Detekce tváře Rozpoznávání tváře Sledovací algoritmy ChokePoint Head Pose Image Dataset OpenCV Dlib Haar LBP CNN HOG Face detection Face recognition tracking algorithm ChokePoint Head Pose Image Dataset OpenCV Dlib Haar LBP CNN HOG T

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Atmospheric Rivers and Associated Precipitation over France and Western Europe: 1980-2020 Climatology and Case Study

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ATMOSPHERE 2021年第8期12卷 1075-1075页

作者： Doiteau, Benjamin Dournaux, Meredith Montoux, Nadege Baray, Jean-Luc Univ Clermont Auvergne CNRS Lab Meteorol Phys UMR 6016 F-63178 Aubiere France Univ Clermont Auvergne CNRS Observ Phys Globe Clermont Ferrand UAR 833 F-63178 Aubiere France

Atmospheric rivers are important atmospheric features implicated in the global water vapor budget, the cloud distribution, and the associated precipitation. The ARiD (Atmospheric River Detector) code has been developed to automatically detect atmospheric rivers from water vapor flux and has been applied to the ECMWF ERA5 archive over the period 1980-2020 above the Atlantic Ocean and Europe. A case study of an atmospheric river formed in the East Atlantic on August 2014 that reached France has been detailed using ECMWF ERA5 reanalysis, ground based observation data, and satellite products such as DARDAR, AIRS, GPCP, and GOES. This atmospheric river event presents a strong interaction with an intense upper tropospheric jet stream, which induced stratosphere-troposphere exchanges by tropopause fold. A 1980-2020 climatology of atmospheric rivers over Europe has been presented. The west of France, Iberian Peninsula, and British Islands are the most impacted regions by atmospheric rivers with an occurrence of up to four days per month during the October-April period. Up to 40% of the precipitation observed on the west European coast can be linked to the presence of ARs. No significant trend in the occurrence of the phenomena was found over 1980-2020.

关键词： atmospheric river water vapor precipitation upper tropospheric jet-stream stratosphere-troposphere exchange tracking algorithm

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The Implementation of Information Processing algorithm for Intelligent Video Surveillance System

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AGRO FOOD INDUSTRY HI-TECH 2017年第3期28卷 1788-1791页

作者： Jing Jing-Xia Henan Univ Anim Husb & Econ Dept Informat Engn Zhengzhou Henan Peoples R China

The application of modern intelligent video surveillance system was more and more, and in this paper, an adaptive background model based on color space transformation was constructed and the shadow elimination algorithm was optimized. In particular, when the target detection was completed by the RGB space, the detection of the foreground target would be locked to the active contour rectangle. And its real-time tracking was obtained;the target's shadow brightness information was used in the elimination of HSV space. It could be seen from the analysis of the final policy that the algorithm could achieve the goal of video tracking under the condition of changing the size of the target or occlusion. Compared with the traditional algorithm, it had a good advantage.

关键词： Intelligent video surveillance tracking algorithm information processing Camshift algorithm

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Research on three-dimensional counting algorithm of high-precision suspended cells based on deep learning

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JOURNAL OF ELECTRONIC IMAGING 2022年第4期31卷 043018-043018页

作者： Sun, Yinbo Guo, Xiaoliang Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing Peoples R China

The research on the three-dimensional counting algorithm of suspension cells is very important for the online counting of cells. Suspension cells are usually observed and counted by taking out cell samples under the microscope. This method cannot realize the online counting of cells. At the same time, there will be weak movement of suspended cells in three-dimensional space, making space counting more difficult. Aiming at the above difficulties, a three-dimensional counting algorithm of suspended cells based on deep learning is proposed. The Faster regions with convolutional neural network (R-CNN) framework is used to identify the target cells, the feature pyramid structure is introduced to reduce the feature loss in the fusion process, and the soft non-maximum suppression algorithm is used to remove the bounding box to improve the detection effect. To reduce the manual labeling workload, an automatic labeling method is proposed. The improved Faster RCNN framework achieves the F1-score of more than 98% after identifying cells, and our method is more accurate than other advanced methods. In terms of three-dimensional counting algorithms, the cells are spatially tracked. Cell matching and correction are carried out by extracting multiple feature information of cells, and adhesion cells are extracted separately for priority processing. The algorithm carried out a tracking experiment on the image sequences of five groups of suspended cells, and the final tracking accuracy of the experiment reached more than 95%. The tracking accuracy is better than other advanced algorithms. Experimental results show that the algorithm achieves high-precision three-dimensional tracking and counting of suspended cells.

关键词： faster regions with convolutional neural network cell counting high-precision tracking algorithm suspension cell

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Video pulse rate variability analysis in stationary and motion conditions

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BIOMEDICAL ENGINEERING ONLINE 2018年第1期17卷 11-11页

作者： Melchor Rodriguez, Angel Ramos-Castro, J. Univ Politecn Cataluna Dept Elect Engn Grp Biomed & Elect Instrumentat Jordi Girona 1-3 ES-08034 Barcelona Spain

Background: In the last few years, some studies have measured heart rate (HR) or heart rate variability (HRV) parameters using a video camera. This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. To date, most of these works have obtained HRV parameters in stationary conditions, and there are practically no studies that obtain these parameters in motion scenarios and by conducting an in-depth statistical analysis. Methods: In this study, a video pulse rate variability (PRV) analysis is conducted by measuring the pulse-to-pulse (PP) intervals in stationary and motion conditions. Firstly, given the importance of the sampling rate in a PRV analysis and the low frame rate of commercial cameras, we carried out an analysis of two models to evaluate their performance in the measurements. We propose a selective tracking method using the Viola-Jones and KLT algorithms, with the aim of carrying out a robust video PRV analysis in stationary and motion conditions. Data and results of the proposed method are contrasted with those reported in the state of the art. Results: The webcam achieved better results in the performance analysis of video cameras. In stationary conditions, high correlation values were obtained in PRV parameters with results above 0.9. The PP time series achieved an RMSE (mean +/- standard deviation) of 19.45 +/- 5.52 ms (1.70 +/- 0.75 bpm). In the motion analysis, most of the PRV parameters also achieved good correlation results, but with lower values as regards stationary conditions. The PP time series presented an RMSE of 21.56 +/- 6.41 ms (1.79 +/- 0.63 bpm). Conclusions: The statistical analysis showed good agreement between the reference system and the proposed method. In stationary conditions, the results of PRV parameters were improved by our method in comparison with data reported in related works. An overall comparative analysis of PRV parameters in motion conditions was more limited due to the lac

关键词： Heart rate variability (HRV) Pulse rate variability (PRV) Imaging photoplethysmography (iPPG) Sampling rate Region of interest (ROI) tracking algorithm Stationary condition Motion scenario

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Multi-Sensory Data Fusion in Terms of UAV Detection in 3D Space

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SENSORS 2022年第12期22卷 4323-4323页

作者： Dudczyk, Janusz Czyba, Roman Skrzypczyk, Krzysztof Stefan Batory State Univ Inst Informat Technol & Tech Sci PL-96100 Skierniewice Poland Silesian Tech Univ Dept Automat Control & Robot PL-44100 Gliwice Poland

The paper focuses on the problem of detecting unmanned aerial vehicles that violate restricted airspace. The main purpose of the research is to develop an algorithm that enables the detection, identification and recognition in 3D space of a UAV violating restricted airspace. The proposed method consists of multi-sensory data fusion and is based on conditional complementary filtration and multi-stage clustering. On the basis of the review of the available UAV detection technologies, three sensory systems classified into the groups of passive and active methods are selected. The UAV detection algorithm is developed on the basis of data collected during field tests under real conditions, from three sensors: a radio system, an ADS-B transponder and a radar equipped with four antenna arrays. The efficiency of the proposed solution was tested on the basis of rapid prototyping in the MATLAB simulation environment with the use of data from the real sensory system obtained during controlled UAV flights. The obtained results of UAV detections confirmed the effectiveness of the proposed method and theoretical expectations.

关键词： UAV anti-drone system data fusion drone detection identification recognition sensing technologies tracking algorithm

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210 Validation of a semi-automatic coronary vessel tracker algorithm for magnetic resonance whole-heart angiography

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Journal of Cardiovascular Magnetic Resonance 2008年第1期10卷 1-3页

作者： Jeroen Sonnemans Raymond Habets Javier Olivan-Bescos Philips Medical Systems Best The Netherlands

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Automated quantification of optokinetic responses based on head-movement

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BMC Neuroscience 2012年第1期13卷 1-2页

作者： Friedrich Kretschmer Jutta Kretzberg Computational Neuroscience Institute of Biology and Environmental Sciences University of Oldenburg D-26111 Oldenburg Germany

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A Comparison of Northern Hemisphere Atmospheric Rivers Detected by a New Image-Processing Based Method and Magnitude-Thresholding Based Methods

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ATMOSPHERE 2020年第6期11卷 628-628页

作者： Xu, Guangzhi Ma, Xiaohui Chang, Ping Wang, Lin Ocean Univ China Inst Adv Ocean Studies Key Lab Phys Oceanog Qingdao 266100 Peoples R China Qingdao Natl Lab Marine Sci & Technol Qingdao 266100 Peoples R China Texas A&M Univ Int Lab High Resolut Earth Syst Predict College Stn TX 77843 USA Texas A&M Univ Dept Oceanog College Stn TX 77843 USA Texas A&M Univ Dept Atmospher Sci College Stn TX 77843 USA Chinese Acad Sci Ctr Monsoon Syst Res Inst Atmospher Phys Beijing 100029 Peoples R China Ocean Univ China Key Lab Phys Oceanog Qingdao Peoples R China

A majority of the existing atmospheric rivers (ARs) detection methods is based on magnitude thresholding on either the integrated water vapor (IWV) or integrated vapor transport (IVT). One disadvantage of such an approach is that the predetermined threshold does not have the flexibility to adjust to the fast changing conditions where ARs are embedded. To address this issue, a new AR detection method is derived from an image-processing algorithm that makes the detection independent of AR magnitude. In this study, we compare the North Pacific and Atlantic ARs tracked by the new detection method and two widely used magnitude thresholding methods in the present day climate. The results show considerable sensitivities of the detected AR number, shape, intensities and their accounted IVT accumulations to different methods. In many aspects, ARs detected by the new method lie between those from the two magnitude thresholding methods, but stand out with a greater number of AR tracks, longer track durations, and stronger AR-related moisture transport in the AR tracks. North Pacific and North Atlantic ARs identified by the new method account for around 100-120 x 10(3) kg/m/s IVT within the AR track regions, about 50%more than the other two methods. This is primarily due to the fact that the new method captures the strong IVT signals more effectively.

关键词： atmospheric river storm tracks tracking algorithm

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Identification of Physical Rapidly Time-Varying Parameters

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IFAC Proceedings Volumes 1994年第8期27卷 645-650页

作者： V.Y. Katkovnik University of South Africa Department of Statistics POBox 392 Pretoria 0001 RSA

The unknown time-varying parameters of physical laws which govern the dynamics of processes can be obtained from measured input and output signals in a local polynomial approximation procedure. Off-line algorithm is developed. The a priori amplitude information about parameters and their derivatives is incorporated to improve the accuracy of the estimation. Mean square errors (MSE) asymptotic with respect to a small sampling period and small window size are presented for the estimates of a fairly arbitrary class of time-varying parameters and their derivatives for the case when the nonlinear dynamics depends on derivatives of the parameters in question.

关键词： Estimation identification mean square errors time-varying systems tracking algorithm

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