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6th International Conference on Signal and Image processing, ICSIP 2021

作者： Chen, Xiaojia Ye, Rihong Wang, Miaohui Shenzhen Institute of Artificial Intelligence and Robotics For Society and Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen China

ISBN: (纸本)9780738133737

Table tennis serving (TTS) machine can effectively reduce the burden of coach and improve the training effect. However, most of the existing TTS systems are generally fixed on the table to serve the balls, and they are pre-programmed and lack of flexibility. To address above problems, we develop an orbital TTS system, which can flexibly move with the human body. Specifically, an improved face detection method is designed to track the human position by introducing the attention mechanism. Moreover, a single branch connection is adopted to reduce the running memory requirement, and a multi-threading scheme is employed to reduce the computing time. Practical experiments show that the developed TTS system has a better flexibility and a higher serving ball quality. © 2021 IEEE.

关键词： Face recognition

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Expression-Aware Masking and Progressive Decoupling for Cross-Database Facial Expression Recognition

Expression-Aware Masking and Progressive Decoupling for Cros...

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International Conference on Automatic Face and Gesture Recognition

作者： Tao Zhong Xiaole Xian Zihan Wang Weicheng Xie Linlin Shen Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University

ISBN: (数字)9798350394948

ISBN: (纸本)9798350394955

Cross-database facial expression recognition (CD-FER) has been widely studied due to its promising applicability in real-life situations, while the generalization performance is the main concern in this task. For improving cross-database generalization, current works frequently resort to masked auto encoder (MAE) to learn the expression representation in an unsupervised manner, and disentanglement of expression and domain features. (i) For MAE, current algorithms mainly employ random masking, and leverage the reconstruction of these masked regions to enable networks to learn the expression representation. However, these masked regions are expression-irrelevant, can not well reflect the characteristics of expression, thus are not efficient enough in representation learning. To this end, we propose an expression-aware masking in MAE to improve the learning efficiency of expression representation, by guiding MAE to mask out expression-aware regions during training. (ii) For disentanglement of expression and domain features, current algorithms realize it mainly in the deep layers. However, the coupling of these features in the shallow layers are rarely concerned, which may largely affect the disentanglement performance in deep layers. Thus, we propose a progressive decoupler to disentangle these features block by block, to use the feature disentanglement in shallow layers to facilitate that in deep layers. Extensive quantitative and qualitative results on multiple expression datasets show that our method can largely outperform the state of the arts in terms of cross-database generalization performance.

关键词： Training Representation learning Couplings Face recognition Gesture recognition Task analysis

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Multi-Class Industrial Texture-less Object Detection Method in Cluttered and Occluded Scenes 5

Multi-Class Industrial Texture-less Object Detection Method ...

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5th World Robot Conference Symposium on Advanced robotics and Automation, WRC SARA 2023

作者： Li, Sicong Zhu, Feng Wu, Qingxiao Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automatio Chinese Academy of Sciences Shenyang China Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350307320

in industrial scenes, template matching algorithms have the advantages of robustness and fastness, but most of them tend to focus on single-class object detection. When facing multi-class object detection tasks, the performance degrades significantly. Deep neural networks are naturally suitable for this task, but rotation regression is still a problem that has yet to be solved perfectly, making it challenging to meet the requirements of industrial robot sorting and grasping scenes. We proposed a hybrid two-stage method called key-pair matching (KPM) algorithm, which can perform robust, fast, and accurate detection of multi-class industrial workpieces. In the first stage, we choose one off-the-shelf CNN detector to predict the horizontal bounding boxes to solve the classification and coarse localization problems in complex scenarios, in the second stage, features based on key-shapes primitives are used to calculate translations and rotations. Experiments show that our proposed method outperform the other comparison methods regarding detection performance and localization accuracy under reasonable runtime, making it suitable for industrial objects detection in cluttered and occlusion scenes. © 2023 IEEE.

关键词： Object detection

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Image saliency detection method based on multi-feature maps fusion 4

Image saliency detection method based on multi-feature maps ...

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4th International Conference on Computer Graphics, Image, and Virtualization, ICCGIV 2024

作者： Li, Xiaoli Liu, Yunpeng Zhao, Huaici Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Opto-Electronic Information Processing Shenyang China The Key Lab of Image Understanding and Computer Vision Shenyang China Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781510683242

In this research, we introduce an innovative saliency detection algorithm, comprising three essential steps. Firstly, leveraging fully convolutional networks with aggregation interaction modules, we generate an initial saliency map. Secondly, we extract hand-craft and deep features to express the image, then use manifold ranking method to construct saliency maps. Ultimately, by integrating the outcomes from preceding stages, we generate the final saliency map. Experimental findings demonstrate that our method surpasses twelve cutting-edge saliency detection techniques in terms of precision, recall, F-measure, and MAE value metrics." © 2024 SPIE.

关键词： Feature extraction

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Study of Sparse Terahertz Synthetic Aperture Imaging Algorithm 3

Study of Sparse Terahertz Synthetic Aperture Imaging Algorit...

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3rd International Conference on Defence Technology, ICDT 2022

作者： Wang, Ningbo Qi, Feng Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

For the terahertz synthetic aperture near-field imaging problem, this paper proposes a SAR imaging method based on sparse reconstruction, which solves the problems of slow scanning speed, a large amount of data, and complicated calculations in the terahertz synthetic aperture imaging process. The targets in space are sparsely sampled and reconstructed using a compressed sensing reconstruction method. Simulation results show that high-quality target reconstruction can be achieved at low sampling conditions. © Published under licence by IOP Publishing Ltd.

关键词： Synthetic apertures

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Focal plane imaging system based on CMOS terahertz detector

Focal plane imaging system based on CMOS terahertz detector

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2024 International Conference on intelligent Manufacturing and Mechatronics, IMM 2024

作者： Lin, Yue Zhang, Hui Qi, Feng Liu, Zhaoyang Wang, Guanwen Wang, Ningbo School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences China The Key Laboratory of Liaoning Province in Terahertz Imaging and Sensing Shenyang China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China The Key Laboratory of OptoElectronic Information Processing Chinese Academy of Sciences Shenyang China School of Information Science and Engineering Shenyang University of Technology Shenyang China

Terahertz technology has shown remarkable potential for application in the field of imaging since it offers several particular advantages such as great penetration capabilities, non-ionization and high instantaneous bandwidth. This paper presents a focal plane imging system based on CMOS terathertz detector for forward-looking detection. The focal plane imaging system has several advantages, including fast scanning, simple composition, low cost, and easy integration of a CMOS detector. It is composed of a terahertz radiation source, a Polytetrafluoroethylene (PTFE) lens and a broadband CMOS detector. The detector was fabricated in a 65 nm CMOS process. The operating frequency range of the detector covers 75 GHz to 1000 GHz. Measurement results have shown that the focal plane imaging system is capable of stably imaging at frequencies of 100 GHz and 220 GHz. To address the issue of missing information in measurement images, the morphological closing algorithm is employed to process the original image, successfully filling in the missing information and improving image quality. © 2024 institute of Physics Publishing. All rights reserved.

关键词： Focusing

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Domain-Invariant Similarity Activation Map Contrastive Learning for Retrieval-Based Long-Term Visual Localization

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 313-328页

作者： Hanjiang Hu Hesheng Wang Zhe Liu Weidong Chen Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China IEEE Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Computer Science and Technology University of CambridgeCambridge CB30FDUnited Kingdom

Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environmental conditions,e.g.,illumination changes,retrievalbased visual localization is severely affected and becomes a challenging *** this work,a general architecture is first formulated probabilistically to extract domain-invariant features through multi-domain image ***,a novel gradientweighted similarity activation mapping loss(Grad-SAM)is incorporated for finer localization with high *** also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised *** final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models with and without Grad-SAM *** experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons *** strong generalization ability of our approach is verified with the RobotCar dataset using models pre-trained on urban parts of the CMU-Seasons *** performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision,especially under challenging environments with illumination variance,vegetation,and night-time ***,real-site experiments have been conducted to validate the efficiency and effectiveness of the coarse-to-fine strategy for localization.

关键词： Deep representation learning place recognition visual localization

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Hou, Muyang Lei, Zhenya Hu, Haidong Wang, Zhong Wang, Yong Xie, Le Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Beijing Institute of Control Engineering Beijing100190 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant;on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A∗ which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion. © 2024 IEEE.

关键词： Trajectories

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Seven Benefits of Using Series Elastic Actuators in the Design of an Affordable, Simple Controlled, and Functional Prosthetic Hand

Seven Benefits of Using Series Elastic Actuators in the Desi...

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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Erfan Koochakzadeh Alireza Kargar Parsa Sattari Diba Ravanshid Rezvan Nasiri Research Institute for Robotics Artificial Intelligence and Information Science (RAIIS) Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper highlights the benefits of using series elastic actuators (SEA) in designing a cost-efficient, easily controlled, and functional prosthetic hand. The designed 3D-printed hand uses only two motors in an antagonistic configuration, transferring power to the fingers via pulleys, cables, and springs; i.e., the motors are in an SEA configuration with the load/fingers. In the designed underactuated prosthetic hand, the thumb is adjustable for various tasks, and the optimization of pulley diameters ensures synchronized finger movement during hand flexion and extension. Thanks to the SEA configuration of the motors and fingers, simple position control of the motor enables features like hand position control, morphological grasp, force control, impedance control, slippage detection, safe interaction, and efficient grasp. An extensive set of experiments has been conducted to evaluate the designed prosthetic hand’s performance. The experiments confirm the hand’s satisfactory performance while also highlighting the importance of improving the proposed design in different aspects. To attain better position control and morphological grasp, minimizing the cable-body and joint friction is recommended. A higher resolution of the current/torque sensor is needed for the precise force control and slippage detection. Finally, a motor brake system is required to achieve efficient grasping.

关键词： Hands Actuators Pulleys Thumb Position control Motors Synchronization Force control Springs Prosthetic hand

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A method for estimating the contribution of an object to scene semantics 4

A method for estimating the contribution of an object to sce...

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4th International Conference on Computer Vision and information Technology, CVIT 2023

作者： Lin, Zhiyuan Zhu, Feng Wang, Jianyu Wang, Qun Zhao, Pengfei Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Robot Science and Engineering Northeastern University Shenyang110169 China

ISBN: (纸本)9781510672864

The amount of semantic contribution of each object in an image to understand the scene is different. Understanding the relative importance of objects in a scene for scene semantics is critical for various computer vision applications, such as scene recognition and image captioning. In this paper, we refer to the contribution of an object to scene semantics as the degree of its gist and propose a method for Estimating the degree of the Gist of an Instance (EGoI). In the EGoI method, an object gist degree is estimated by the semantic features comparison strategy and the semantic distance comparison strategy. In the first strategy, the image is represented as a scene graph first, then the aggregation features and the node features of different graph node combinations are calculated to estimate the instance gist that is not in the combination of the nodes. In the second strategy, the captions of the complete and incomplete images are generated, then the semantic distance of these captions is used to estimate the instance gist deleted in the scene. Different strategies for estimating the gist degree of instances are tested in the experiments. The results show that the proposed method can effectively quantify the contribution of an instance to scene semantics. Among these strategies, the method that compares semantic features has better discriminative power for the gist degree of various instances in the scene. © 2024 SPIE.

关键词： Semantics

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