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 >

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 >

Jianchu Lin^1,2, Shuang Li³, Hong Qin^3,4, Hongchang Wang³, Ning Cui⁶, Qian Jiang⁷, Haifang Jian^3,*, Gongming Wang^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1621-1651, 2023, DOI:10.32604/cmes.2022.020857

Abstract 3D human pose estimation is a major focus area in the field of computer vision, which plays an important role in practical applications. This article summarizes the framework and research progress related to the estimation of monocular RGB images and videos. An overall perspective of methods integrated with deep learning is introduced. Novel image-based and video-based inputs are proposed as the analysis framework. From this viewpoint, common problems are discussed. The diversity of human postures usually leads to problems such as occlusion and ambiguity, and the lack of training datasets often results in poor generalization ability of the model. Regression… More >

Hyun Yoo¹, Kyungyong Chung^2,*

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 1-13, 2022, DOI:10.32604/iasc.2022.024890

Abstract Human pose estimation has been a major concern in the field of computer vision. The existing method for recognizing human motion based on two-dimensional (2D) images showed a low recognition rate owing to motion depth, interference between objects, and overlapping problems. A convolutional neural network (CNN) based algorithm recently showed improved results in the field of human skeleton detection. In this study, we have combined human skeleton detection and deep neural network (DNN) to classify the motion of the human body. We used the visual geometry group network (VGGNet) CNN for human skeleton detection, and the generated skeleton coordinates were… More >

Ayesha Arif¹, Yazeed Yasin Ghadi², Mohammed Alarfaj³, Ahmad Jalal¹, Shaharyar Kamal¹, Dong-Seong Kim^4,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1-18, 2022, DOI:10.32604/cmc.2022.023553

Abstract In the new era of technology, daily human activities are becoming more challenging in terms of monitoring complex scenes and backgrounds. To understand the scenes and activities from human life logs, human-object interaction (HOI) is important in terms of visual relationship detection and human pose estimation. Activities understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been explained. Some existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures, occluded regions, and unsatisfactory detection of objects, especially small-sized objects. The existing HOI detection techniques are instance-centric (object-based)… More >