An improved object tracking algorithm based on adaptive weighted strategy and occlusion detection mechanism

Due to complex background and volatile object shape-appearance in image, the stability and accuracy of tracking algorithm is often disturbed and reduced. So how to accurately and robustly track object in object tracking application is a challenge topic at home and abroad. Built upon the methodologies of compressive tracking and spatio-temporal context, a simple yet robust object tracking method is proposed for solving the drift and occlusion problems in paper. It combines two existing classical ideas into a single framework: adaptive weighted idea and occlusion detection mechanism. In order to weaken interference problems of object background, object area is firstly partitioned into equal-sized sub-patches and the different weight related with location information is assigned for each patch; Then, for improving its robustness, Bhattacharyya distance is adopted to find out these samples with maximum discrimination; In addition, our proposed occlusion detection mechanism is for recapturing the tracked object when occlusion occurs. Many simulation experiments show that our proposed algorithm achieves more favorable performance than these existing state-of-the-art algorithms in handing various challenging infrared videos, especially occlusion and shape deformation.

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An Improved Object Tracking Algorithm Combining Spatio-Temporal Context and Selection Update

2020 Chinese Automation Congress (CAC) ◽

10.1109/cac51589.2020.9327712 ◽

2020 ◽

Author(s):

Da Zhang ◽

Enzeng Dong ◽

Hang Yu ◽

Chao Jia

Keyword(s):

Object Tracking ◽

Tracking Algorithm ◽

Temporal Context ◽

Spatio Temporal

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A scale-adaptive object-tracking algorithm with occlusion detection

EURASIP Journal on Image and Video Processing ◽

10.1186/s13640-020-0496-6 ◽

2020 ◽

Vol 2020 (1) ◽

Cited By ~ 6

Author(s):

Yue Yuan ◽

Jun Chu ◽

Lu Leng ◽

Jun Miao ◽

Byung-Gyu Kim

Keyword(s):

Object Tracking ◽

Tracking Algorithm ◽

Occlusion Detection

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Object Tracking Algorithm based on Improved Context Model in Combination with Detection Mechanism for Suspected Objects

Multimedia Tools and Applications ◽

10.1007/s11042-018-7025-y ◽

2019 ◽

Vol 78 (12) ◽

pp. 16907-16922 ◽

Cited By ~ 3

Author(s):

Xiuyan Tian ◽

Haifang Li ◽

Hongxia Deng

Keyword(s):

Object Tracking ◽

Tracking Algorithm ◽

Context Model ◽

Detection Mechanism

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DDAT Target Tracking Algorithm Based on Occlusion Detection Mechanism

Laser & Optoelectronics Progress ◽

10.3788/lop57.241501 ◽

2020 ◽

Vol 57 (24) ◽

pp. 241501

Author(s):

周维 Zhou Wei ◽

唐华龙 Tang Hualong ◽

李观德 Li Guande ◽

刘宇翔 Liu Yuxiang

Keyword(s):

Target Tracking ◽

Tracking Algorithm ◽

Occlusion Detection ◽

Detection Mechanism

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Underground Microseismic Event Monitoring and Localization within Sensor Networks

Sensors ◽

10.3390/s21082830 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2830

Author(s):

Sili Wang ◽

Mark P. Panning ◽

Steven D. Vance ◽

Wenzhan Song

Keyword(s):

Sensor Networks ◽

Real Time ◽

Information Needs ◽

Localization Algorithm ◽

Distributed Sensors ◽

Distributed Sensor ◽

Microseismic Events ◽

The Stability ◽

Stability And Accuracy

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.

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Spatio-temporal selection of reference genes in the two congeneric species of Glycyrrhiza

Scientific Reports ◽

10.1038/s41598-020-79298-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yuping Li ◽

Xiaoju Liang ◽

Xuguo Zhou ◽

Yu An ◽

Ming Li ◽

...

Keyword(s):

Gene Expression ◽

Developmental Stage ◽

Reference Genes ◽

Developmental Stages ◽

Individual Factors ◽

Congeneric Species ◽

Spatio Temporal ◽

The Stability ◽

Different Tissues ◽

Selection Of

AbstractGlycyrrhiza, a genus of perennial medicinal herbs, has been traditionally used to treat human diseases, including respiratory disorders. Functional analysis of genes involved in the synthesis, accumulation, and degradation of bioactive compounds in these medicinal plants requires accurate measurement of their expression profiles. Reverse transcription quantitative real-time PCR (RT-qPCR) is a primary tool, which requires stably expressed reference genes to serve as the internal references to normalize the target gene expression. In this study, the stability of 14 candidate reference genes from the two congeneric species G. uralensis and G. inflata, including ACT, CAC, CYP, DNAJ, DREB, EF1, RAN, TIF1, TUB, UBC2, ABCC2, COPS3, CS, R3HDM2, were evaluated across different tissues and throughout various developmental stages. More importantly, we investigated the impact of interactions between tissue and developmental stage on the performance of candidate reference genes. Four algorithms, including geNorm, NormFinder, BestKeeper, and Delta Ct, were used to analyze the expression stability and RefFinder, a comprehensive software, provided the final recommendation. Based on previous research and our preliminary data, we hypothesized that internal references for spatio-temporal gene expression are different from the reference genes suited for individual factors. In G. uralensis, the top three most stable reference genes across different tissues were R3HDM2, CAC and TUB, while CAC, CYP and ABCC2 were most suited for different developmental stages. CAC is the only candidate recommended for both biotic factors, which is reflected in the stability ranking for the spatio (tissue)-temporal (developmental stage) interactions (CAC, R3HDM2 and DNAJ). Similarly, in G. inflata, COPS3, R3HDM2 and DREB were selected for tissues, while RAN, COPS3 and CS were recommended for developmental stages. For the tissue-developmental stage interactions, COPS3, DREB and ABCC2 were the most suited reference genes. In both species, only one of the top three candidates was shared between the individual factors and their interactions, specifically, CAC in G. uralensis and COPS3 in G. inflata, which supports our overarching hypothesis. In summary, spatio-temporal selection of reference genes not only lays the foundation for functional genomics research in Glycyrrhiza, but also facilitates these traditional medicinal herbs to reach/maximize their pharmaceutical potential.

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Explicit parallel co-simulation approach: analysis and improved coupling method based on H-infinity synthesis

Multibody System Dynamics ◽

10.1007/s11044-021-09785-x ◽

2021 ◽

Author(s):

Weitao Chen ◽

Shenhai Ran ◽

Canhui Wu ◽

Bengt Jacobson

Keyword(s):

Frequency Domain ◽

Wide Frequency Range ◽

Coupling Method ◽

Sampled Data ◽

H Infinity ◽

First Case ◽

Communication Step ◽

Coupling Variables ◽

The Stability ◽

Stability And Accuracy

AbstractCo-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system.In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation.

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A Digital Framework to Predict the Sunshine Requirements of Landscape Plants

Applied Sciences ◽

10.3390/app11052098 ◽

2021 ◽

Vol 11 (5) ◽

pp. 2098

Author(s):

Heyi Wei ◽

Wenhua Jiang ◽

Xuejun Liu ◽

Bo Huang

Keyword(s):

Solar Radiation ◽

Plant Species ◽

Large Scale ◽

Normal Growth ◽

Adaptive Selection ◽

Landscape Plant ◽

Landscape Plants ◽

The Stability ◽

Stability And Accuracy ◽

The City

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.

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