Qingsong Fan, Qijie Rao, Haisong Huang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1825-1848, 2023, DOI:10.32604/cmes.2023.028369

Abstract In present-day industrial settings, where robot arms perform tasks in an unstructured environment, there may exist numerous objects of various shapes scattered in random positions, making it challenging for a robot arm to precisely attain the ideal pose to grasp the object. To solve this problem, a multistage robotic arm flexible grasp detection method based on deep learning is proposed. This method first improves the Faster RCNN target detection model, which significantly improves the detection ability of the model for multiscale grasped objects in unstructured scenes. Then, a Squeeze-and-Excitation module is introduced to design a multitarget grasping pose generation network… More >

Meng Xu¹, Chen Shen², Jun Zhang², Zhipeng Wang³, Zhiwei Ruan², Stefan Poslad¹, Pengfei Xu^2,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4785-4803, 2023, DOI:10.32604/cmc.2023.034053

Abstract As the fundamental problem in the computer vision area, image matching has wide applications in pose estimation, 3D reconstruction, image retrieval, etc. Suffering from the influence of external factors, the process of image matching using classical local detectors, e.g., scale-invariant feature transform (SIFT), and the outlier filtering approaches, e.g., Random sample consensus (RANSAC), show high computation speed and pool robustness under changing illumination and viewpoints conditions, while image matching approaches with deep learning strategy (such as HardNet, OANet) display reliable achievements in large-scale datasets with challenging scenes. However, the past learning-based approaches are limited to the distinction and quality of… More >

Jian Kang¹, Wanshu Fan¹, Yijing Li², Rui Liu¹, Dongsheng Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 607-629, 2023, DOI:10.32604/cmes.2023.024420

Abstract With the advancement of image sensing technology, estimating 3D human pose from monocular video has become a hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequent action analysis and understanding. It empowers a wide spectrum of potential applications in various areas, such as intelligent transportation, human-computer interaction, and medical rehabilitation. Currently, some methods for 3D human pose estimation in monocular video employ temporal convolutional network (TCN) to extract inter-frame feature relationships, but the majority of them suffer from insufficient inter-frame feature relationship extractions. In this paper, we decompose the 3D joint location regression… More >

Jia-Yu Liang¹, Hong-Bo Zhang^1,*, Qing Lei², Ji-Xiang Du³, Tian-Liang Lin⁴

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3243-3256, 2023, DOI:10.32604/iasc.2023.035812

Abstract Monocular 6D pose estimation is a functional task in the field of computer vision and robotics. In recent years, 2D-3D correspondence-based methods have achieved improved performance in multiview and depth data-based scenes. However, for monocular 6D pose estimation, these methods are affected by the prediction results of the 2D-3D correspondences and the robustness of the perspective-n-point (PnP) algorithm. There is still a difference in the distance from the expected estimation effect. To obtain a more effective feature representation result, edge enhancement is proposed to increase the shape information of the object by analyzing the influence of inaccurate 2D-3D matching on… More >

Jaspreet Chawla^1,*, Anil Kr Ahlawat²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2787-2802, 2023, DOI:10.32604/iasc.2023.034775

Abstract Cloud computing has become one of the leading technologies in the world today. The benefits of cloud computing affect end users directly. There are several cloud computing frameworks, and each has ways of monitoring and providing resources. Cloud computing eliminates customer requirements such as expensive system configuration and massive infrastructure while improving dependability and scalability. From the user’s perspective, cloud computing makes it easy to upload multiagents and operate on different web services. In this paper, the authors used a restful web service and an agent system to discuss, deployments, and analysis of load performance parameters like memory use, central… More >

Mi Zhou¹, Rui Liu^1,*, Pengfei Yi¹, Dongsheng Zhou^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 2093-2109, 2023, DOI:10.32604/cmes.2023.024189

Abstract Multi-view multi-person 3D human pose estimation is a hot topic in the field of human pose estimation due to its wide range of application scenarios. With the introduction of end-to-end direct regression methods, the field has entered a new stage of development. However, the regression results of joints that are more heavily influenced by external factors are not accurate enough even for the optimal method. In this paper, we propose an effective feature recalibration module based on the channel attention mechanism and a relative optimal calibration strategy, which is applied to the multi-view multi-person 3D human pose estimation task to… More > Graphic Abstract

Ching-Bang Yao¹, Chang-Yi Kao^2,*, Jiong-Ting Lin³

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2233-2252, 2023, DOI:10.32604/iasc.2023.034488

Abstract Traditional monitoring systems that are used in shopping malls or community management, mostly use a remote control to monitor and track specific objects; therefore, it is often impossible to effectively monitor the entire environment. When finding a suspicious person, the tracked object cannot be locked in time for tracking. This research replaces the traditional fixed-point monitor with the intelligent drone and combines the image processing technology and automatic judgment for the movements of the monitored person. This intelligent system can effectively improve the shortcomings of low efficiency and high cost of the traditional monitor system. In this article, we proposed… More >

K. Ishwarya, A. Alice Nithya^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6081-6099, 2023, DOI:10.32604/cmc.2023.034654

Abstract Human pose estimation (HPE) is a procedure for determining the structure of the body pose and it is considered a challenging issue in the computer vision (CV) communities. HPE finds its applications in several fields namely activity recognition and human-computer interface. Despite the benefits of HPE, it is still a challenging process due to the variations in visual appearances, lighting, occlusions, dimensionality, etc. To resolve these issues, this paper presents a squirrel search optimization with a deep convolutional neural network for HPE (SSDCNN-HPE) technique. The major intention of the SSDCNN-HPE technique is to identify the human pose accurately and efficiently.… More >

Manahil Waheed¹, Samia Allaoua Chelloug^2,*, Mohammad Shorfuzzaman³, Abdulmajeed Alsufyani³, Ahmad Jalal¹, Khaled Alnowaiser⁴, Jeongmin Park⁵

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5853-5870, 2023, DOI:10.32604/cmc.2023.033769

Abstract Identifying human actions and interactions finds its use in many areas, such as security, surveillance, assisted living, patient monitoring, rehabilitation, sports, and e-learning. This wide range of applications has attracted many researchers to this field. Inspired by the existing recognition systems, this paper proposes a new and efficient human-object interaction recognition (HOIR) model which is based on modeling human pose and scene feature information. There are different aspects involved in an interaction, including the humans, the objects, the various body parts of the human, and the background scene. The main objectives of this research include critically examining the importance of… More >

Chafaa Hamrouni^1,2,*, Aarif Alutaybi¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6445-6460, 2023, DOI:10.32604/cmc.2023.026441

Abstract Several assessing efforts are approved making both communication and information technologies available. In addition to being a part of universal access and service, we aim at assessing the impact of radio access technologies on universal access indicators. The proposed work demonstrates the possibility of inter-working of all existing Radio Access Technologies (RATs), in a limited area presented in the Six Generation Radio Resources Allocation (6 G-A) network. We propose a solution for the Vertical hand Over (VHO) in 6 G-A heterogeneous system, that adopts Media Independent Handover (MIH) protocol to benefit between different used technologies in a direct communication firstly… More >