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Action Status Based Novel Relative Feature Representations for Interaction Recognition

Chinese Journal of Electronics 2022年第1期31卷 168-180页

作者： LI Yanshan GUO Tianyu LIU Xing LUO Wenhan XIE Weixin ATR National Key Laboratory of Defense Technology Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Tencent

Skeleton-based action recognition has always been an important research topic in computer vision. Most of the researchers in this field currently pay more attention to actions performed by a single person while there is very little work dedicated to the identification of interactions between two people. However, the practical application of interaction recognition is actually more critical in our society considering that actions are often performed by multiple people. How to design an effective scheme to learn discriminative spatial and temporal representations for skeleton-based interaction recognition is still a challenging problem. Focusing on the characteristics of skeleton data for interactions, we first define the moving distance to distinguish the action status of the participants. Then some view-invariant relative features are proposed to fully represent the spatial and temporal relationship of the skeleton sequence. Further, a new coding method is proposed to obtain the novel relative feature representations. Finally, we design a three-stream CNN model to learn deep features for interaction recognition. We evaluate our method on SBU dataset, NTU RGB+D 60 dataset and NTU RGB+D 120 dataset. The experimental results also verify that our method is effective and exhibits great robustness compared with current state-of-the-art methods.

关键词： image representation relative feature representations skeleton-based interaction recognition skeleton sequence skeleton data image coding deep learning (artificial intelligence) image recognition temporal representations temporal relationship view-invariant relative features spatial relationship skeleton-based action recognition action status computer vision convolutional neural nets discriminative spatial representations image motion analysis

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An Adaptive Parallel Gaussian Homotopy Approach for Zeroth-Order Optimization

An Adaptive Parallel Gaussian Homotopy Approach for Zeroth-O...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhou, Bingyi Wang, Guoyou Huazhong University of Science and Technology National Key Laboratory of Multispectral Information Intelligent Processing Technology Wuhan China

ISBN: (纸本)9781665410205

The Gaussian homotopy method is a classical optimization approach for solving nonconvex problems. It applies Gaussian smoothing to a given problem, using varying smoothing factors to generate a series of proxy problems that are easier to solve, subsequently addressing them gradually from simpler to more complex ones. Traditional Gaussian homotopy methods typically utilize a predefined sequence or parameter to update a single smoothing factor serially. However, this sequential updating process is inefficient and unsuitable for parallel homotopy pipelines. Moreover, the utilization of predefined sequences or parameters leads to a lack of adaptability. To address the abovementioned challenges, we propose an adaptive parallel Gaussian homotopy optimization method. Initially, we introduce an adaptive model called Scaling. This model is formulated as a scaler that concurrently adjusts multiple smoothing factors, with each factor aligning to a homotopy level. It can be integrated easily into serial and parallel homotopy pipelines. Furthermore, we establish a collaborative training regimen to jointly train the Scaling model and a parallel homotopy model, named continuation path learning (CPL) [1] model. Throughout the training process, the Scaling model furnishes CPL with multiple scaled smoothing factors and updates CPL implicitly. Extensive experiments demonstrate that the proposed Gaussian homotopy approach performs competitively. © 2024 IEEE.

关键词： Gaussian distribution

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An anti-occlusion tracking algorithm based on mask strategy and adaptive response fusion 12

An anti-occlusion tracking algorithm based on mask strategy ...

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SPIE 12th International Symposium on Multispectral Image processing and Pattern Recognition, MIPPR 2023

作者： Duan, Zhongyu Huang, Shixiang Yue, Zhongmu Tian, Tian Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

In long-Term target tracking, target occlusion is an important factor that affects the performance of the tracker, and it is also an inevitable problem in long-Term target tracking. Therefore, it is necessary to adopt corresponding strategies for target occlusion to improve the robustness of the tracker in corresponding scenarios. In response to the problem of target loss in complex background scenarios such as target occlusion in current filtering based tracking algorithms, this paper studies the use of masking strategies and adaptive response fusion methods to improve the accuracy and robustness of tracking *** experimental results demonstrate the effectiveness of various strategies in resisting occlusion in tracking algorithms. The experimental results of the overall algorithm indicate that the algorithm can effectively solve occlusion problems while balancing accuracy, speed, and robustness. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Target tracking

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Selecting matching area based on deep learning keypoint features 12

Selecting matching area based on deep learning keypoint feat...

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SPIE 12th International Symposium on Multispectral Image processing and Pattern Recognition, MIPPR 2023

作者： Ding, Tian Tian, Tian Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

Selecting the appropriate matching area is one of the crucial tasks in scene matching systems, serving as the basis for trajectory planning. Currently, there are two main approaches for adaptation zone selection: Traditional statistical feature-based adaptation zone selection methods and deep learning-based adaptation zone selection methods. The former relies on multi-Threshold screening to choose adaptation zones, resulting in a complex and less accurate process. The latter employs model training to select adaptation zones, improving accuracy, but it tends to yield less stable results. Therefore, this paper utilizes the *** network to extract keypoints and their feature descriptors within the scene region as the initial feature set. It employs support vector regression as the matching probability prediction model and uses threshold segmentation on the predicted probabilities to ultimately determine the adaptability of the region. Experimental results demonstrate that the adaptation zone selection method proposed in this paper offers higher accuracy and stability. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Navigation

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Side-Channel Leakage Analysis of Inner Product Masking

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Computers, Materials & Continua 2024年第4期79卷 1245-1262页

作者： Yuyuan Li Lang Li Yu Ou College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang421002China

The Inner Product Masking(IPM)scheme has been shown to provide higher theoretical security guarantees than the BooleanMasking(BM).This scheme aims to increase the algebraic complexity of the coding to achieve a higher level of *** previous work unfolds when certain(adversarial and implementation)conditions are met,and we seek to complement these investigations by understanding what happens when these conditions deviate from their expected *** this paper,we investigate the security characteristics of IPM under different *** adversarial condition,the security properties of first-order IPMs obtained through parametric characterization are preserved in the face of univariate and bivariate *** implementation condition,we construct two new polynomial leakage functions to observe the nonlinear leakage of the IPM and connect the security order amplification to the nonlinear *** observe that the security of IPMis affected by the degree and the linear component in the leakage *** addition,the comparison experiments from the coefficients,signal-to-noise ratio(SNR)and the public parameter show that the security properties of the IPM are highly implementation-dependent.

关键词： Side-channel analysis inner product masking mutual information nonlinear leakage

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High-precision end-to-end adaptive optics aided orbital angular momentum wireless communication with XFTC-Net

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Optics Letters 2025年第10期50卷 3265-3268页

作者： Xu, Panpan Chang, Huan Wang, Fei Gao, Ran Guo, Dong Zhu, Lei Li, Zhipei Zhou, Sitong Xu, Qi Chen, Jing Xin, Xiangjun Beijing100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China Beijing100876 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology 250353 China

In this Letter, we demonstrate high-precision end-to-end adaptive optics (AO) technique based on the X-Shape Fusion Transformer-convolutional neural network (XFTC-Net) without an additional probe path to compensate for distortions caused by atmospheric turbulence (AT) in orbital angular momentum (OAM) optical wireless communication links. The experimental results show that the XFTC-Net effectively extracts the intensity distribution features of distorted OAM beams, predicting AT phase screens and identifying OAM modes. After XFTC-Net-aided AO compensation, the bit error rate of the OAM optical communication system remains below 3.8 × 10−3, staying within Cn2 = 1 × 10−15–1 × 10−13 m−2/3. Moreover, the optical power with l= 3 increases from 5.08 dBm to 8.23 dBm at a transmission distance of 800 m. These experimental results indicate that the proposed XFTC-Net AO technique effectively compensates for OAM beam distortion in both single- and multiplexed-channel OAM links, which effectively balances the system complexity and transmission performance of OAM-based free space optical (FSO) communication systems, opening up new avenues for enhancing the performances of high-capacity optical communication. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Fiber to the x

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Research and application of composite stochastic resonance in enhancement detection

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Chinese Physics B 2024年第1期33卷 264-273页

作者：高蕊焦尚彬薛琼婕 School of Automation and Information Engineering Xi'an University of TechnologyXi'an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of TechnologyXi'an 710048China

Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently, a new composite stochastic resonance(NCSR) model is proposed by combining the Woods–Saxon(WS) model and the improved piecewise bistable model. The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation, all the parameters in the new model have no coupling characteristics. Under α stable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has higher noise utilization and better detection ***, the new model is applied to image denoising, the results showed that under the same conditions, the output peak signal-to-noise ratio(PSNR) and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods, the effectiveness of the new model is verified.

关键词： Woods–Saxon improved piecewise model composite stochastic resonance(SR) image denoising

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A Review on the Application of Deep Learning Methods in Detection and Identification of Rice Diseases and Pests

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Computers, Materials & Continua 2024年第1期78卷 197-225页

作者： Xiaozhong Yu Jinhua Zheng College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang421002China

In rice production,the prevention and management of pests and diseases have always received special *** methods require human experts,which is costly and *** to the complexity of the structure of rice diseases and pests,quickly and reliably recognizing and locating them is ***,deep learning technology has been employed to detect and identify rice diseases and *** paper introduces common publicly available datasets;summarizes the applications on rice diseases and pests from the aspects of image recognition,object detection,image segmentation,attention mechanism,and few-shot learning methods according to the network structure differences;and compares the performances of existing ***,the current issues and challenges are explored fromthe perspective of data acquisition,data processing,and application,providing possible solutions and *** study aims to review various DL models and provide improved insight into DL techniques and their cutting-edge progress in the prevention and management of rice diseases and pests.

关键词： Deep learning rice diseases and pests image recognition object detection

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SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

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Computers, Materials & Continua 2024年第6期79卷 4641-4657页

作者： Jiahui Liu Lang Li Di Li Yu Ou College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang421002China

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys ***,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within *** challenges significantly hinder key recovery *** paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these ***-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained ***,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each ***,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct ***,an intelligent search method is proposed to identify optimal parameters,further improving attack *** were conducted on both simulated environments and real power traces collected from the SAKURA-G *** the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

关键词： Side-channel analysis correlation power analysis genetic algorithm crossover mutation

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Pseudo-Centroid Representation Learning for Cross-domain Few-shot Classification from Remote Sensing Imagery 2

Pseudo-Centroid Representation Learning for Cross-domain Few...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Li, Can Xie, Jianlin Chen, He Zhuang, Yin Li, Jiahao Chen, Liang Beijing Institute of Technology National Key Laboratory of Space-Born Intelligent Information Processing Beijing China

ISBN: (纸本)9798331515669

Cross-domain few-shot classification is gaining significant attention due to its potential to address challenges in remote sensing applications, such as large domain gaps and limited labeled data. Recent approaches have explored leveraging unlabeled target domain data for semi-supervised learning, in addition to source labeled data, to improve cross-domain training. However, these techniques often struggle with getting discriminative representation for distinguishing categories in novel target domains, particularly when facing new categories and limited training examples. To overcome these issues, we propose a novel cross-domain pseudo-centroid representation (CDPCR) framework, designed to generate more discriminative and adaptable class representations for improved cross-domain learning. The framework consists of a semi-supervised cross-domain structure that integrates both source labeled data and a portion of target unlabeled data to establish the relationship between domains. A consistency regularization branch is introduced to stabilize model outputs by aligning predictions on the target unlabeled data under input perturbations. Additionally, a pseudo-centroid contrastive representation learning module is incorporated to enhance intra-category feature consistency while improving the separability of inter-category representations, aiding the model in adapting to classification tasks across diverse domains. The effectiveness of the proposed CDPCR framework is validated through comprehensive experiments conducted across 8 cross-domain scenarios using remote sensing scene classification datasets. © 2024 IEEE.

关键词： Contrastive Learning

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