On parameterizing higher-order motion for behaviour recognition

Sun, Yan; Hare, Jonathon; Nixon, Mark S.

doi:10.1016/j.patcog.2020.107710

Cited by 4 publications

(3 citation statements)

References 59 publications

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“…In this section, comprehensive weights are computed by combinng the two types of weights, which not only reflect the preference of experts but also the influence of objective indicators. According to the minimum relative entropy [50,51], the weights of each indicator obtained from different methods should be close. Therefore, the objective function is shown in Equation (13).…”

Section: Comprehensive Weight Methodsmentioning

confidence: 99%

Evaluating Expressway Safety Based on Fuzzy Comprehensive Evaluation with AHP–Entropy Method: A Case Study of Jinliwen Expressway in Zhejiang Province, China

Zhang,

Yu,

Mao

et al. 2023

Systems

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To mitigate potential safety hazards during expressway operation, safety evaluation plays a crucial role. This study develops a fuzzy comprehensive evaluation model to assess the safety of expressway operations. First, an expressway operation safety risk assessment index system consisting of four criteria-layer indicators and 10 sub-criteria layer indicators is established. Then, the comprehensive weight of each evaluation index is calculated based on the combined AHP and entropy methods. Finally, the expressway safety level is obtained by converting qualitative indicators into fuzzy sets and defining corresponding membership functions to describe their degree of membership. The evaluation model is applied to the Jinliwen Expressway in a mountainous area in Zhejiang Province, China. The results show that the method could quantitatively and comprehensively evaluate the safety status of expressways and identify the weak links of operational safety management, which can effectively improve the safety level of expressway operations. The research findings will assist decision-makers in gaining a better understanding of the safety issues of expressways and, thus, using corresponding measures to enhance the safety level of the expressway.

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Section: Comprehensive Weight Methodsmentioning

confidence: 99%

Evaluating Expressway Safety Based on Fuzzy Comprehensive Evaluation with AHP–Entropy Method: A Case Study of Jinliwen Expressway in Zhejiang Province, China

Zhang,

Yu,

Mao

et al. 2023

Systems

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“…The comprehensive weight should be as close as possible to the subjective weight and objective weight, but not to any of them. This paper determines the comprehensive weight based on the principle of minimum discrimination information [21]. This principle will select a new distribution to replace the original distribution and ensure that the difference between the new distribution and the original distribution is as small as possible.…”

Section: Comprehensive Empowerment Theorymentioning

confidence: 99%

Hydropower Unit State Evaluation Model Based on AHP and Gaussian Threshold Improved Fuzzy Comprehensive Evaluation

et al. 2023

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Because a single monitoring index cannot fully reflect the overall operating status of the hydropower unit, a comprehensive state evaluation model for hydropower units based on the analytic hierarchy process (AHP) and the Gaussian threshold improved fuzzy evaluation is proposed. First, the unit equipment was divided into a hierarchical system, and a three-tier structure system (target layer-project layer-index layer) of the unit was constructed, and the weight of each component in the system was determined by the comprehensive weighting method. Secondly, according to the characteristics of the normal distribution of the historical health data of the unit, the upper and lower limits of the index were determined based on the Gaussian threshold principle, the real-time monitoring index degradation degree was calculated according to the index limit, and the degradation degree was applied to the fuzzy evaluation model to obtain the fuzzy judgment matrix. The result of assessment was divided into four sections: good, qualified, vigilant, and abnormal. Finally, combined with the unit hierarchical structure system, the weighted calculation of the fuzzy judgment matrix of each indicator, the overall fuzzy judgment matrix of the upper-level indicators of the unit was obtained, and the operating status of the unit was judged according to the matrix. Taking a real power plant unit as an example, the model was verified, and compared with other evaluation methods, the effectiveness and advantages of the proposed method were verified. In addition, the method proposed in this paper effectively solved the problems of index weighting and index limit determination in the existing model of unit condition evaluation.

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“…Human Action Recognition (HAR) is a thriving domain of research that is still progressing on account of its versatile applicability in various elds like video surveillance [1], health care [2], human behavior understanding [3], crowd assessment [4], anomaly detection [5] etc. Video surveillance through drones is one of the intensively focused applications of action recognition as drones offer a perfect solution to video surveillance owing to its low cost, mobility and wide area coverage compared to traditional cameras.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Aerial Human Action Recognition through GAN-boosted ResNeXt Architecture with Squeeze-and-Excitation Network

Kapoor,

Sharma,

Verma

2023

Preprint

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Recognizing human actions in aerial videos captured by Unmanned Aerial Vehicles (UAVs) presents a significant challenge due to reduced resolution and blurry appearance of humans. To address this, we propose a novel two-module system, GAN-SE, that tackles these limitations and achieves remarkable improvements in human action recognition. The first module employs a super-resolution GAN to enhance the low-resolution images of detected humans. By generating high-resolution images, our system recovers lost information and significantly enhances the visual quality of the detections, thereby improving the accuracy of action recognition. In second module, we introduce a Squeeze and Excitation (SE) network combined with ResNeXt101 model to effectively calibrate the correlation between channel features. The SE network adaptively recalibrates feature responses in a channel-wise manner, enabling our model to focus on the most relevant information in feature maps. This leads to superior feature representation and more accurate predictions. To evaluate the performance of GAN-SE, extensive experiments were conducted on three challenging datasets: Aeriform in-action, UCF-ARG, and Okutama-Action. The results demonstrate the effectiveness of our system, achieving an accuracy of 80.78%, 97.36%, and 77.50% on the respective datasets. These results outperform the state-of-the-art methods, reaffirming the superiority of GAN-SE in aerial human action recognition.

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On parameterizing higher-order motion for behaviour recognition

Cited by 4 publications

References 59 publications

Evaluating Expressway Safety Based on Fuzzy Comprehensive Evaluation with AHP–Entropy Method: A Case Study of Jinliwen Expressway in Zhejiang Province, China

Evaluating Expressway Safety Based on Fuzzy Comprehensive Evaluation with AHP–Entropy Method: A Case Study of Jinliwen Expressway in Zhejiang Province, China

Hydropower Unit State Evaluation Model Based on AHP and Gaussian Threshold Improved Fuzzy Comprehensive Evaluation

Enhancing Aerial Human Action Recognition through GAN-boosted ResNeXt Architecture with Squeeze-and-Excitation Network

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