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A Point Cloud Segmentation Method Based on Ground Point Cloud Removal and Multi-Scale Twin Range Image

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A Point Cloud Segmentation Method Based on Ground Point Clou...

Chinese control Conference (CCC)

作者： Yicheng Zhou Gang Peng Hangqi Duan Zhangang Wu Xukang Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China Shantui Construction Machinery Co. Ltd. Jining China

Aiming at the shortcomings of traditional point cloud segmentation algorithms, this paper proposes a 3D lidar point cloud segmentation method combining ground filtering and multi-scale twin range image construction. This method fully considers the geometric space distribution characteristics of the point cloud and the randomness of the positions between objects. Based on the assumption of multi plane model, the point cloud is divided into sectors. The ground points are removed through region ground plane fitting and growth, and then the multi-scale twin range image is constructed according to non-ground points. On the basis of the twin range image, the Breadth First Search algorithm is improved, the depth-breadth joint search strategy is proposed, all the points to be clustered are traversed, and the adaptive clustering threshold is used for point cloud clustering, which realizes a point cloud segmentation method with higher accuracy and robustness. Through the experimental analysis of KITTI dataset and collected campus outdoor scene dataset, compared with the traditional point cloud segmentation algorithm, the method proposed in this paper can effectively improve the point cloud segmentation accuracy and robustness of mobile robots in complex environments.

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Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression

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arXiv 2023年

作者： Pan, Zhiyu Chen, Yinpeng Zhang, Jiale Lu, Hao Cao, Zhiguo Zhong, Weicai Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Huawei CBG Consumer Cloud Service Search Product & Big Data Platform Department China

Automatic image cropping algorithms aim to recompose images like human-being photographers by generating the cropping boxes with improved composition quality. Cropping box regression approaches learn the beauty of composition from annotated cropping boxes. However, the bias of annotations leads to quasi-trivial recomposing results, which has an obvious tendency to the average location of training samples. The crux of this predicament is that the task is naively treated as a box regression problem, where rare samples might be dominated by normal samples, and the composition patterns of rare samples are not well exploited. Observing that similar composition patterns tend to be shared by the cropping boundaries annotated nearly, we argue to find the beauty of composition from the rare samples by clustering the samples with similar cropping boundary annotations, i.e., similar composition patterns. We propose a novel Contrastive Composition Clustering (C2C) to regularize the composition features by contrasting dynamically established similar and dissimilar pairs. In this way, common composition patterns of multiple images can be better summarized, which especially benefits the rare samples and endows our model with better generalizability to render nontrivial results. Extensive experimental results show the superiority of our model compared with prior arts. We also illustrate the philosophy of our design with an interesting analytical visualization. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

Lifetime Extension control for Multi-Stack SOFC System with Inconsistent Stacks

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Lifetime Extension Control for Multi-Stack SOFC System with ...

Chinese control Conference (CCC)

作者： Zexin Li Guoqiang Liu Wei Zhao Xi Li Key Laboratory of Image Processing and Intelligent Control of Education Ministry School of Artificial Intelligence and Automation Huazhong University of Science & Technology Wuhan Hubei China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen Guangdong China

The multi-stack fuel cell system (MFCS) is an important basis for the application of solid oxide fuel cell (SOFC) technology to large-scale power generation systems. MFCS can provide higher power, longer lifetime and better reliability. Different from the single-stack fuel cell system (SFCS), there may be some inconsistencies among the stacks in the MFCS. If the inconsistencies are ignored, they will significantly affect the lifetime of the MFCS. This study focuses on the lifetime extension of multi-stack SOFC power generation systems with inconsistent stacks. Since the multi-stack system of SOFC generally cannot control the flow rate of each stack respectively, it brings a difficulty to the control of the MFCS with inconsistencies among the stacks. In order to overcome this difficulty, this paper built a multi-stack SOFC system model, which can characterize the degradation and inconsistencies among SOFC stacks. And then designed a power distribution strategy based on fuzzy control to extend the lifetime of the MFCS. The strategy was verified by simulations. The simulation results show that the strategy can effectively control the inconsistencies among the stacks and significantly extend the lifetime of the MFCS.

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Semi-Supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMix

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arXiv 2023年

作者： Wang, Kewei Wu, Yizheng Pan, Zhiyu Li, Xingyi Xian, Ke Wang, Zhe Cao, Zhiguo Lin, Guosheng S-Lab Nanyang Technological University Singapore Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China SenseTime Research Hong Kong

Class-agnostic motion prediction methods aim to comprehend motion within open-world scenarios, holding significance for autonomous driving systems. However, training a high-performance model in a fully-supervised manner always requires substantial amounts of manually annotated data, which can be both expensive and time-consuming to obtain. To address this challenge, our study explores the potential of semi-supervised learning (SSL) for class-agnostic motion prediction. Our SSL framework adopts a consistency-based self-training paradigm, enabling the model to learn from unlabeled data by generating pseudo labels through test-time inference. To improve the quality of pseudo labels, we propose a novel motion selection and re-generation module. This module effectively selects reliable pseudo labels and regenerates unreliable ones. Furthermore, we propose two data augmentation strategies: temporal sampling and BEVMix. These strategies facilitate consistency regularization in SSL. Experiments conducted on nuScenes demonstrate that our SSL method can surpass the self-supervised approach by a large margin by utilizing only a tiny fraction of labeled data. Furthermore, our method exhibits comparable performance to weakly and some fully supervised methods. These results highlight the ability of our method to strike a favorable balance between annotation costs and performance. Code will be available at https://***/kwwcv/SSMP. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

Constraining Depth Map Geometry for Multi-View Stereo: A Dual-Depth Approach with Saddle-shaped Depth Cells

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arXiv 2023年

作者： Ye, Xinyi Zhao, Weiyue Liu, Tianqi Huang, Zihao Cao, Zhiguo Li, Xin Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science University of Albany AlbanyNY12222 United States

Learning-based multi-view stereo (MVS) methods deal with predicting accurate depth maps to achieve an accurate and complete 3D representation. Despite the excellent performance, existing methods ignore the fact that a suitable depth geometry is also critical in MVS. In this paper, we demonstrate that different depth geometries have significant performance gaps, even using the same depth prediction error. Therefore, we introduce an ideal depth geometry composed of Saddle-Shaped Cells, whose predicted depth map oscillates upward and downward around the ground-truth surface, rather than maintaining a continuous and smooth depth plane. To achieve it, we develop a coarse-to-fine framework called Dual-MVSNet (DMVSNet), which can produce an oscillating depth plane. Technically, we predict two depth values for each pixel (Dual-Depth), and propose a novel loss function and a checkerboard-shaped selecting strategy to constrain the predicted depth geometry. Compared to existing methods,DMVSNet achieves a high rank on the DTU benchmark and obtains the top performance on challenging scenes of Tanks and Temples, demonstrating its strong performance and generalization ability. Our method also points to a new research direction for considering depth geometry in MVS. Copyright © 2023, The Authors. All rights reserved.

关键词： Geometry

Fast Full-frame Video Stabilization with Iterative Optimization

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arXiv 2023年

作者： Zhao, Weiyue Li, Xin Peng, Zhan Luo, Xianrui Ye, Xinyi Lu, Hao Cao, Zhiguo Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science University of Albany AlbanyNY12222 United States

Video stabilization refers to the problem of transforming a shaky video into a visually pleasing one. The question of how to strike a good trade-off between visual quality and computational speed has remained one of the open challenges in video stabilization. Inspired by the analogy between wobbly frames and jigsaw puzzles, we propose an iterative optimization-based learning approach using synthetic datasets for video stabilization, which consists of two interacting submodules: motion trajectory smoothing and full-frame outpainting. First, we develop a two-level (coarse-to-fine) stabilizing algorithm based on the probabilistic flow field. The confidence map associated with the estimated optical flow is exploited to guide the search for shared regions through backpropagation. Second, we take a divide-and-conquer approach and propose a novel multiframe fusion strategy to render full-frame stabilized views. An important new insight brought about by our iterative optimization approach is that the target video can be interpreted as the fixed point of nonlinear mapping for video stabilization. We formulate video stabilization as a problem of minimizing the amount of jerkiness in motion trajectories, which guarantees convergence with the help of fixed-point theory. Extensive experimental results are reported to demonstrate the superiority of the proposed approach in terms of computational speed and visual quality. The code will be available on GitHub. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

An Effective and Real-time Time-Slot Power Detection Method 23

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An Effective and Real-time Time-Slot Power Detection Method

Proceedings of the 3rd International Conference on Electronic Information Technology and Smart Agriculture

作者： Xian Zhang Xinhui Luo Taiguo Qu Dong Yin School of Computer and Artificial Intelligence (School of Software) Huaihua University China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China and Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China Department of Art Design Huaihua Tourism School China School of Computer and Artificial Intelligence (School of Software) Huaihua University China

ISBN: (纸本)9798400716775

To efficiently detect the time-slot power of the Time Division Multiple Access (TDMA) communication systems such as repeaters and base stations in real-time. This article designs a signal-sampling hardware circuit based on the Advanced RISC Machine (ARM) platform and proposes a comprehensive method to calculate the time-slot power values. The signal sampling circuit uses the ADC108S052 chip with an 8-channel linked to the ARM via the Serial Peripheral Interface (SPI), and the time-slot power detection approach consists of a signal timing sampling module, sampling data reading module, and sampling data processing module to compute the detected time-slot power comprehensively. We design experiments to evaluate the efficacy of the approach to detect the time-slot power with the system power-on and normality running condition, the detection of the system CPU resource consumption for the time-slot power, the detection of the error value for the time-slot power, etc. The experimental results demonstrate that the approach can be efficient, and real-time detection of the time-slot power of the TDMA system, the system of repeaters and base stations and other systems of signal coverage, optimization and so on is of great significance.

关键词： ARM Analog-to-Digital Converter (ADC) Signal sampling Time division multiple access Time slot power

Transmission-Constrained Consensus of Multiagent Networks

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arXiv 2022年

作者： Wang, Xiaotian Su, Housheng School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

This paper studies the consensus problem for multiagent systems with transmission constraints. A novel model of multiagent systems is proposed where the information transmissions between agents are disturbed by irregular distortions or interferences (named transmission constraint functions), and this model is universal which can be applied in many cases, such as interval consensus and discarded consensus. In the transmission-constrained consensus problem, we obtain the necessary and sufficient condition that agents can converge to state consensus. Furthermore, a more general case is studied in which the system reaches an equilibrium. Based on some techniques of algebraic topology and stability theory, the existence, uniqueness and stability of the system equilibrium point can be proven, which means the system can reach an asymptotically stable equilibrium. Moreover, the state values of the equilibrium are only decided by the network structure and transmission constraint functions, but not the agents’ initial states. Finally, numerical simulations are presented to illustrate the proposed theorems and corollaries. © 2022, CC BY-NC-SA.

关键词： Directed graphs

Distributed Resource Allocation via Accelerated Saddle Point Dynamics

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1588-1599页

作者： Wen-Ting Lin Yan-Wu Wang Chaojie Li Xinghuo Yu School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of EducationHuazhong University of Science and TechnologyWuhan 430074China School of Electrical Engineering and Telecommunications University of New South WalesSydney NSW 2052Australia School of Engineering Royal Melbourne Institute of Technology(RMIT University)Melbourne VIC 3000Australia

In this paper,accelerated saddle point dynamics is proposed for distributed resource allocation over a multi-agent network,which enables a hyper-exponential convergence ***,an inertial fast-slow dynamical system with vanishing damping is introduced,based on which the distributed saddle point algorithm is *** dual variables are updated in two time scales,i.e.,the fast manifold and the slow *** the fast manifold,the consensus of the Lagrangian multipliers and the tracking of the constraints are pursued by the consensus *** the slow manifold,the updating of the Lagrangian multipliers is accelerated by inertial ***-exponential stability is defined to characterize a faster convergence of our proposed algorithm in comparison with conventional primal-dual algorithms for distributed resource *** simulation of the application in the energy dispatch problem verifies the result,which demonstrates the fast convergence of the proposed saddle point dynamics.

关键词： Accelerated saddle point dynamic distributed resource allocation hyper-exponential stability power dispatch