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GRAMO:geometric resampling augmentation for monocular 3D object detection

Frontiers of Computer Science 2024年第5期18卷 161-169页

作者： He GUAN Chunfeng SONG Zhaoxiang ZHANG School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence SystemsInstitute of Automation Chinese Academy of SciencesBeijing 100190China

Data augmentation is widely recognized as an effective means of bolstering model ***,when applied to monocular 3D object detection,non-geometric image augmentation neglects the critical link between the image and physical space,resulting in the semantic collapse of the extended *** address this issue,we propose two geometric-level data augmentation operators named Geometric-Copy-Paste(Geo-CP)and Geometric-Crop-Shrink(Geo-CS).Both operators introduce geometric consistency based on the principle of perspective projection,complementing the options available for data augmentation in monocular ***,Geo-CP replicates local patches by reordering object depths to mitigate perspective occlusion conflicts,and Geo-CS re-crops local patches for simultaneous scaling of distance and scale to unify appearance and *** operations ameliorate the problem of class imbalance in the monocular paradigm by increasing the quantity and distribution of geometrically consistent *** demonstrate that our geometric-level augmentation operators effectively improve robustness and performance in the KITTI and Waymo monocular 3D detection benchmarks.

关键词： 3D detection monocular augmentation geometry

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Pre-trained Language Model - Based Real-time Formation Lithology Identification Method for Drilling Process

Pre-trained Language Model - Based Real-time Formation Litho...

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2024 China automation Congress, CAC 2024

作者： Liu, Jianyang Gan, Chao Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

Geological exploration is essential for economic and social progress, with lithology identification being a key technology that improves exploration precision and resource development efficiency. This paper presents a real-time identification method of formation lithology in drilling process based on pre-training language model, which is divided into three stages. In this first stage, the drilling data undergoes rigorous cleaning, feature selection, and normalization to eliminate noise and anomalies. In the second stage, key model inputs such as weight on bit (WOB), rate of penetration (ROP), rotation speed (RPM), torque, and pump volume (P) are identified through detailed drilling mechanism analysis. In the last stage, a real-time identification method of formation lithology in drilling process based on pre-training language model is proposed, which realizes high-precision real-time identification in drilling process. The effectiveness of the proposed method is proved by comparison with common methods. © 2024 IEEE.

关键词： Lithology

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A Review on 3D Hand Pose and Shape Reconstruction from Color Images 43

A Review on 3D Hand Pose and Shape Reconstruction from Color...

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43rd Chinese control Conference, CCC 2024

作者： Leng, Huajian Ge, Yuting Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

The task of hand reconstruction aims to estimate the shape and pose of hands from the input images. Deep learning algorithms have shown remarkable performance in the field of computer vision in recent years, promoting the development of related algorithms. This article reviews the 3D hand reconstruction technologies, introducing the research background, value, and directions, summarizing the characteristics of datasets and evaluation metrics, and discussing the types of parametric, non-parametric, and joint mesh representation methods;it then outlines research directions in single-hand, hand-object interaction, and two-hand reconstruction, and analyzes their progress. Finally, it summarizes both the hand datasets and the algorithms, and provides a perspective on the future development of hand reconstruction. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： 3D reconstruction

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Non-Convex Operating Zone Establishment and Alarm Limit Design for Multivariate Alarm Systems Based on Grid Clustering 43

Non-Convex Operating Zone Establishment and Alarm Limit Desi...

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43rd Chinese control Conference, CCC 2024

作者： Wei, Yujie Hu, Wenkai Li, Yupeng Cao, Weihua China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Alarm systems are core components in large complex industrial facilities to ensure safe and efficient operation. Traditional univariate alarm system design methods ignore the correlation of process variables and thus may generate massive false alarms and missed alarms. An effective way of designing a multivariate alarm system is to establish the normal operating zones (NOZs) based on historical data under normal conditions. These NOZs serve as the basis for setting alarm limits in multivariate alarm systems. Given that the actual correlations between related variables are frequently unknown, a robust modeling approach is necessary to effectively handle both convex and non-convex NOZs. Thus, this paper presents a systematic method for nonconvex operating zone establishment and alarm limit design for multivariate alarm systems. A multivariate non-convex NOZ is established based on grid clustering. Then, the multidimensional grid boundary is extracted and used to determine the alarm limits for real-time samples. A numerical example is used to demonstrate the effectiveness of the proposed method. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Alarm systems

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A Lightweight Steel Strip Defect Detection Method Based on YOLO 43

A Lightweight Steel Strip Defect Detection Method Based on Y...

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43rd Chinese control Conference, CCC 2024

作者： Qian, Hao Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

As an essential component of modern industry, steel strips play an indispensable role in various fields and serve as a crucial raw material in industrial production. However, due to various factors such as production technology, the surface of steel strips often exhibits unavoidable defects like scratches and crazings. Therefore, implementing online surface quality inspection for steel strips is one effective way to enhance product quality and production efficiency. This paper proposes a detection method for surface defects in steel strips based on YOLO. By optimizing the network structure of YOLOv5s, the performance on the NEU-DET dataset has improved by nearly 4 % compared to the original network's mAP value. Experimental results indicate that the detection performance of this method is significantly superior to the current mainstream lightweight detection networks. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Strip metal

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Adaptive-Critic-Based Event-Triggered intelligent Cooperative control for a Class of Second-Order Constrained Multiagent Systems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第6期4卷 1654-1665页

作者： Guo, Zijie Ren, Hongru Li, Hongyi Zhou, Qi Guangdong University of Technology School of Automation Guangzhou510006 China Guangdong University of Technology Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China Peng Cheng Laboratory Department of New Networks Shenzhen518055 China

An event-based intelligent cooperative control policy is developed in this article for a class of second-order multiagent systems (MASs). The followers are subject to external disturbances and output constraints, in which the constraint ranges are asymmetric and time-varying. By using one-to-one nonlinear mapping technique to obtain equivalent unconstrained systems and designing a distributed observer to estimate the leader's states, a simplified unconstrained tracking control task is established for each follower. After that, event-driven distributed optimal H∞ controllers are designed to mitigate the effects of external disturbances, which are obtained from a set of decoupled Hamilton-Jacobi-Isaacs (HJI) equations, where the proposed event-triggered strategy is dynamic. Aiming at solving the HJI equations more efficiently, an event-based adaptive dynamic programming (ADP) learning algorithm applying only critic neural networks (NNs) is developed. And the critic NN weights are convergent by using stored data under finite excitation condition. Finally, the validity of the developed control scheme is demonstrated by multiple single-link robot arm systems. © 2020 IEEE.

关键词： Multi agent systems

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Animatable Human Neural Radiance Field from Sparse Images Captured by a Single Camera 43

Animatable Human Neural Radiance Field from Sparse Images Ca...

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43rd Chinese control Conference, CCC 2024

作者： Yang, Qingru Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Recently, the use of neural radiance fields (NeRF) for three-dimensional reconstruction of humans has achieved high-quality view rendering. However, existing methods often rely on multiple or single videos as input, requiring dense images, and the rendering quality tends to be poor with sparse image inputs. To address this issue, this paper proposes a novel method that solely utilizes sparse images captured by a single camera to create an animatable human neural radiance field, enabling the rendering of high-fidelity human images under arbitrary novel viewpoints and poses. Specifically, our method utilizes body poses and multi-view feature to build a deformable neural radiance field, and employs frequency-segmented positional encoding to mitigate overfitting during training process. Extensive quantitative and qualitative experiments demonstrate that our proposed method outperforms prior works. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Image reconstruction

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A Detector-Free Image Matching Method based on Enhanced Feature Fusion 43

A Detector-Free Image Matching Method based on Enhanced Feat...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Ziyang Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Eduction Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

Image feature matching is an important research field in computer vision that can be widely applied to advanced vision tasks, such as 3D reconstruction and visual tracking. Considering the low matching accuracy and poor robustness of traditional detector-based matching methods on weakly textured images, we propose a detector-free image matching method based on enhanced feature fusion. Given that weak texture images consist of a large number of similar or irregular pixels, we introduce a new model that enhances feature fusion to recover the underlying texture information of the image. First, we propose a bidirectional fusion model to extract multi-scale feature maps and add an initialization module to correlate the feature maps and enhance the representation ability of the backbone. Then, we perform feature transformation using the quadtree attention model and finally establish dense pixel-by-pixel matching at both coarse and fine scales. The quadtree attention model employs a hierarchical computational attention method, accurately capturing image details and remote dependencies while ensuring linear complexity. Experimental results demonstrate that the proposed method achieves higher matching accuracy and better generalization on large datasets such as MegaDepth and ScanNet, making it suitable for subsequent work. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Image matching

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Accurate and rapid image segmentation method for bayberry automatic picking via machine learning

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International Journal of Agricultural and Biological Engineering 2023年第6期16卷 246-254页

作者： Huan Lei Chentong Li Yu Tang Zhenyu Zhong Zeyu Jiao Institute of Intelligent Manufacturing Guangdong Academy of SciencesGuangzhou 510070China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of ScienceGuangzhou 510070China School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China

Due to the short ripening period and complex picking environment,bayberry generally relies on mechanical equipment for picking,especially the automatic picking system guided by ***,it is crucial to locate the bayberry in the view accurately and *** efforts have been made,the existing methods are difficult to implement due to the limited amount of data and the processing *** this study,an accurate and rapid segmentation method based on machine learning was proposed to address this ***,the images collected by the visual guidance system were pre-processed by contrast-limited adaptive histogram equalization(CLAHE)based on the Y component of the YUV color *** advantage of the color difference map of RB and RG for the segmentation of different colors,an adaptive color difference map foreground segmentation method was then adopted for bayberry region foreground ***,distance transforms and marking control watershed methods were exploited to achieve single bayberry fruit ***,with the help of the convex hull theory and fruit shape characteristics,the irregular background interference areas were filtered out,which improved the accuracy of bayberry segmentation *** experimental results show that this method can achieve better segmentation of bayberry in complex orchard environment with an accuracy of 97.4%and only takes 0.136 s to calculate once.

关键词： bayberry image segmentation machine learning automatic picking computer vision

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Data-driven consensus control of fully distributed event-triggered multi-agent systems

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Science China(Information Sciences) 2023年第5期66卷 147-161页

作者： Yifei LI Xin WANG Jian SUN Gang WANG Jie CHEN School of Automation Beijing Institute of Technology The State Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This study investigates the consensus control issue in discrete-time linear multi-agent systems(MASs) using data-driven control under undirected communication networks. To alleviate the communication burden, an adaptive event-triggered control strategy involving only local information is proposed and a model-based stability condition is derived that guarantees the asymptotic consensus of MASs. Furthermore,a data-based consensus condition for unknown MASs is established by combining a data-based system representation with the model-based stability condition, using only pre-collected noisy input-state data instead of the accurate system information a priori. Specifically, both model-based and data-driven event-triggered controllers can be utilized without requiring any global information. The validity and correctness of the controllers and associated theoretical results are demonstrated via numerical simulations.

关键词： distributed control event-triggered control data-driven control discrete-time MASs

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