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Hand Gesture Recognition from an Open-Set Perspective

IEEE Transactions on Multimedia 2025年

作者： Zhou, Jun Xu, Chi Cheng, Li China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Vision and Learning Laboratory Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

Existing hand gesture recognition methods predominantly rely on a close-set assumption, which in essence limits the viewpoints, gesture categories, and hand shapes at test time to closely resemble those seen during training. This requirement is however rarely met in practice, as images are often captured from unconstrained viewpoints, with novel gestures and unseen hand shapes that can differ significantly from the training data. This motivates us to investigate an open-set hand gesture recognition problem, where hand gestures are still recognizable from unconstrained viewpoints, and novel gesture classes and hand shapes can be incrementally learned with just a few examples. To address this, we propose a viewpoint influence elimination network that extracts view-independent features, significantly improving performance in scenarios with unconstrained viewpoints. Moreover, a joint-weighted classification scheme is introduced to augment the cosine similarity metric for evaluating few-shot incremental learning of novel gestures and shapes. Finally, as existing hand gesture recognition datasets primarily adhere to the close-set assumption, a new hand gesture recognition dataset, OHG, is introduced in this paper, that includes a wide range of viewpoints, diverse gesture classes, and distinct hand shapes. Experimental hand gesture recognition results demonstrate the superior performance of our approach in both unconstrained viewpoint and few-shot incremental learning scenarios. The source code and the OHG dataset are to be made available at https://***/zhoujun-7/OSHGR. © 1999-2012 IEEE.

关键词： Palmprint recognition

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Bionic design of a self-reconfigurable modular robot for search and rescue

Bionic design of a self-reconfigurable modular robot for sea...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Gao, Guangju Liu, Jingshuai He, Yong Sun, Jianquan Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781665436786

This paper proposes a novel self-reconfigurable modular robot for search and rescue. The modular robot consists of two main structures, a planetary wheel driven robot body and a double unlocking system as the docking structure. By means of the planetary wheel structure, the robot has a strong flexibility to cross obstacles in a disaster environment. In virtue of the docking structure with double unlocking function, the self-reconfigurable ability has improved robot reliability. Further, the modular robot can be connected or disconnected according to the actual task requirements. Finally, to verify the stability and reliability, the finite element analysis is carried out. © 2021 IEEE.

关键词： Reliability analysis

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Enhancing ontology-based home Care Services platform using Bayesian networks

Enhancing ontology-based home Care Services platform using B...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Abdelweheb Gueddes Mohamed Ali Mahjoub ISITCom LATIS Laboratory of Advanced Technology and Intelligent Systems Sousse University Sousse Tunisia LATIS Laboratory of Advanced Technology and Intelligent Systems Sousse University National School of Engineers of Sousse Sousse Tunisia

ISBN: (数字)9781728184708

ISBN: (纸本)9781728184715

During the first generation of home intervention and support, complaints were usually triggered by telephone call. In most situations needs where described orally; there were no sufficient information neither on the patient's condition nor on his medical history. Thanks to the advance of technology, especially systems based on data mining, artificial intelligence time is saved, and immediate service is offered. Although home intervention and care have been the subject of numerous studies, the resolution of the overall decision-making problem is not sufficiently developed. Due to the lack of information such as the state of health of a patient, the set of parameters characterizing the daily life habits of the person analyzed in parallel with the evolution of physiological and environmental parameters. In addition to that, it is necessary to take into consideration the Medical Core, his location, his profile not only his professional status, but also his capacities and skills, which are not explicitly described in his curriculum. Different studies and systems exist in literature. Each them takes into account only part of the parameters. Indeed, these studies face either the monitoring of daily activities, the monitoring of physiological data or other environmental part. Either they take into account the specific features of the medical core profile. Either these systems use probabilistic data mining, which involves many interactions with experts to interpret the data, or an expert system based on the rules of inference defined by medical experts. In addition, most do not use controlled vocabulary, which provides semantics to the system. This complicates information sharing and collaborative work. We proposed in a previous work an ontology-based solution [3], the goal is to help the collaborator to make a decision and to draw new information. as the complexity of the data increases, so does the need to deal with uncertainty. Several approaches to the representation and

关键词： Uncertainty Semantics OWL Ontologies Probabilistic logic Data mining Monitoring

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A Novel Multi-Stream Informer Used for Lower Extremity Joint Angle Estimation 12

A Novel Multi-Stream Informer Used for Lower Extremity Joint...

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12th International Conference on CYBER technology in Automation, Control, and intelligent systems, CYBER 2022

作者： Zhou, Xin Zhang, Liming Liu, Jiaqing Ye, Jiancong Wang, Can Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China University of Science and Technology of China China University of Chinese Academy of Sciences China South China University of Technology China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In lower extremity exoskeleton rehabilitation systems, synergy and proportionality between the human lower extremity and the exoskeleton robot have been a critical goal to pursue. In recent years, changeable deep learning models based on multi-source signals have been used for lower limb continuous motion estimation. During the process, multimode signals are fed into the time processing model as time series. However, there are some deficiencies in this framework, on the one hand, what kind of multi-source combination can be more efficient;on the other hand, most of the existing models need several iterations or network stacking to complete the extraction of temporal information. This study set out to address the above problems, we put forward Multi-Stream Informer (MS-Informer), using Multi-Stream combination and sparse attention mechanisms for lower limb continuous motion estimation. In the experiment, we compare MS-Informer and Temporal Convolutional Network (TCN) and Long Short-term Memory (LSTM) under distinctive multi-source combinations. In summary, MS-informer performs well in multiple evaluations compared with other models. Experimental results illustrate that the MS-Informer is more efficacious in lower limb joint angle estimation and is a promising method for achieving coordinated control of lower limb exoskeletons. © 2022 IEEE.

关键词： Motion estimation

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Development of a 3-RRS Micromanipulator Based on Origami-Inspired Spherical Joint

Development of a 3-RRS Micromanipulator Based on Origami-Ins...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haoqi Han Xiaoming Liu Yan Chen Hao Pang Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Micro-Nano Electronics Shanghai Jiao Tong University China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In recent years, micromanipulation technology has achieved extensive applications in industry and life science. Improving the precision and bandwidth of the micromanipulator and simultaneously reducing size, weight, and cost pose significant challenges to the existing micromanipulator design and fabrication methods. Here, we propose a 3-RRS micromanipulator with an origami-inspired spherical joint based on the PC-MEMS process, aiming for miniaturization and cost-effectiveness. The spherical joint allows rotations of 140° around the x-axis approximately, 140° around the y-axis approximately, and 20° around the z-axis approximately. The micromanipulator has weights of 0.8 g, dimensions of 16 mm × 16 mm × 22 mm, and workspace of 0.7 mm 3 . The end platform of the micromanipulator can be equipped with various effectors to accomplish different kinds of tasks. Experimental results validated its high precision and bandwidth, exhibiting its potential to perform intricate micromanipulation tasks.

关键词： Industries Fabrication Costs Micromanipulators Design methodology Bandwidth Life sciences

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Prediction Method of Truck Travel Time in Open Pit Mines Based on LSTM Model

Prediction Method of Truck Travel Time in Open Pit Mines Bas...

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第42届中国控制会议

作者： Mengting Ao Changhe Li Shengxiang Yang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Computer Science and Informatics De Montfort University

Aiming at the prediction of truck travel time in open pit mines,we established a prediction model based on long short-term memory(LSTM).This model fully accounts for 11 factors,including the nature of trucks,weather,road conditions,and driver's behaviors,as well as the influence of neighbor road segments in the route on the current predicted road *** experiment shows that the error of the LSTM prediction model is significantly reduced compared with S VR and BP *** addition,the maximum absolute mean error under different conditions is less than 12 seconds.

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Hydrogel-elastomer-based stretchable strain sensor fabricated by a simple projection lithography method

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International Journal of Smart and Nano Materials 2021年第3期12卷 256-268页

作者： Zhenqing Li Xiangnan He Jianxiang Cheng Honggeng Li Yuan-Fang Zhang Xiaojuan Shi Kai Yu Hui Ying Yang Qi Ge Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhenChina Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and TechnologyShenzhenChina Digital Manufacturing and Design Centre Singapore University of Technology and DesignSingapore Department of Mechanical Engineering University of Colorado DenverDenverCOUSA National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbinP.R.China

Stretchable strain sensor detects a wide range of strain variation and is therefore a key component in various *** traditional ones made of elastomers doped with conductive components or fabricated with liquid conductors,ionically conductive hydrogel-based strain sensors remain conductive under large deformations and are ***,dehydration is a challenging issue for the *** have developed hydrogel-elastomer-based strain sensors where an elastomer matrix encapsulates a hydrogel circuit to prevent its ***,the reported multistep approaches are generally *** group recently reported a multimaterial 3D printing approach that enables fast fabrication of such sensors,yet requires a self-built digital-light-processing-based multimaterial 3D ***,we report a simple projection lithography method to fabricate hydrogel-elastomer-based stretchable strain sensors within 5 *** method only requires a UV projector/lamp with photomasks;the chemicals are commercially available;the protocols for preparing the polymer precursors are friendly to users without chemistry ***,the manufacturing flexibility allows users to readily pattern the sensor circuit and attach the sensor to a 3D printed soft pneumatic actuator to enable strain sensing on the *** proposed approach paves a simple and versatile way to fabricate hydrogel-elastomer-based stretchable strain sensors and flexible electronic devices.

关键词： Ionically conductive hydrogel stretchable strain sensor projection lithography

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Deep Learning-Based Estimation of Arterial Stiffness from PPG Spectrograms: A Novel Approach for Non-Invasive Cardiovascular Diagnostics

Deep Learning-Based Estimation of Arterial Stiffness from PP...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Kiana Pilevar Abrisham Khalil Alipour Bahram Tarvirdizadeh Mohammad Ghamari Department of Mechatronics Engineering School of Intelligent Systems Engineering College of Interdisciplinary Science and Technology Advanced Service Robots (ASR) Laboratory University of Tehran Tehran Iran Department of Electrical and Computer Engineering Kettering University Flint Michigan USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Cardiovascular diseases (CVDs), a leading cause of global mortality, are intricately linked to arterial stiffness, a key factor in cardiovascular health. Non-invasive assessment of arterial stiffness, particularly through Carotid-to-femoral Pulse Wave Velocity (cf-PWV) – the gold standard in this field – is vital for early detection and management of CVDs. This study introduces a novel approach, utilizing photoplethysmogram (PPG) signal spectrograms as inputs for deep learning models to estimate cf-PWV, a significant advancement over traditional methods. Employing a modified ResNet-18 architecture, we analyze PPG signals from digital, radial, and brachial arteries of a simulated dataset of 4374 healthy adults. Our methodology's innovation lies in its direct use of finely tuned spectrogram images, bypassing the complex feature extraction processes. This approach achieved R 2 (correlation coefficient) values of up to 0.9902 for the digital artery, 0.9898 for the radial artery, and 0.9825 for the brachial artery, coupled with significantly lower Mean Absolute Percentage Errors (MAPE) of approximately 1.61% for the digital, 1.87% for the radial, and 2.08% for the brachial artery. These findings highlight the efficacy of PPG spectrograms, especially from the digital artery, in providing an accurate, user-friendly, and non-invasive method for cf-PWV estimation, thereby enhancing the capabilities of non-invasive cardiovascular diagnostics.

关键词： Accuracy Noise Estimation Predictive models Feature extraction Brachytherapy Data models Arteries Spectrogram Monitoring

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Multi view 3D reconstruction method for weak texture objects based on "eye-in-hand" model

Multi view 3D reconstruction method for weak texture objects...

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2021 China Automation Congress, CAC 2021

作者： Gong, Xuan Chen, Xin Jian, Xu He, Wenpeng School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9781665426473

Size measurement and defect detection of ceramics are required in the production process of ceramic products. Therefore, it is necessary to perform high-precision and fast three-dimensional reconstruction of such targets with smooth surfaces and weak textures. However, the reconstruction of a large number of point clouds from multiple perspectives is time-consuming due to the matching of adjacent feature points. Based on this, a fast point cloud registration strategy based on the "eye-in-hand" model is proposed, which can obtain RGB-D images at multi-view around weak-textured objects with RGB-D camera for rapid point cloud registration and reconstruction. Meanwhile, a 3D point cloud segmentation method based on voxel-grid and euclidean distance clustering is applied to divide the scene point and obtain an accurate 3D model. The experimental results indicate that the multi view 3D reconstruction speed of this method is faster and the accuracy of objects point cloud is within 2 mm. Hence, this method can be well applied in reconstructing the 3D point clouds model for ceramic products. © 2021 IEEE

关键词： Textures

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Ultrafast and real-time physical random bit extraction with all-optical quantization

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advanced Photonics 2022年第3期4卷 83-89页

作者： Ya Guo Qiang Cai Pu Li Ruonan Zhang Bingjie Xu K.Alan Shore Yuncai Wang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control SystemsMinistry of EducationTaiyuanChina Guangdong University of Technology School of Information EngineeringGuangdong Provincial Key Laboratory of Photonics Information TechnologyGuangzhouChina Northwestern Polytechnical University School of Electronics and InformationXi’anChina Institute of Southwestern Communication Science and Technology on Communication LaboratoryChengduChina Bangor University School of Electronic EngineeringWalesUnited Kingdom

Optical chaos generated by perturbing semiconductor lasers has been viewed,over recent decades,as an excellent entropy source for fast physical random bit generation(RBG)owing to its high bandwidth and large random ***,most optical-chaos-based random bit generators perform their quantization process in the electrical domain using electrical analog-to-digital converters,so their real-time rates in a single channel are severely limited at the level of Gb/s due to the electronic ***,we propose and experimentally demonstrate an all-optical method for RBG where chaotic pulses are quantized into a physical random bit stream in the all-optical domain by means of a length of highly nonlinear *** our proof-of-concept experiment,a 10-Gb/s random bit stream is successfully generated on-line using our *** that the single-channel real-time rate is limited only by the chaos *** that the Kerr nonlinearity of silica fiber with an ultrafast response of few femtoseconds is exploited for composing the key part of quantizing laser chaos,this scheme thus may operate potentially at much higher real-time rates than 100 Gb/s provided that a chaotic entropy source of sufficient bandwidth is available.

关键词： chaos random number generation semiconductor lasers optical signal processing.

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