Xianhua Li^1,2,*, Haohao Yu¹, Shuoyu Tian¹, Fengtao Lin³, Usama Masood¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3551-3564, 2024, DOI:10.32604/cmc.2024.047336

Abstract The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional (3D) method that takes into account self-occlusion, badly posedness, and a lack of depth data in the per-frame 3D posture estimation from two-dimensional (2D) mapping to 3D mapping. Firstly, by examining the relationship between the movements of different bones in the human body, four virtual skeletons are proposed to enhance the cyclic constraints of limb joints. Then, multiple parameters describing the skeleton are fused and projected into a high-dimensional space. Utilizing a multi-branch network, motion features between bones and overall motion features are extracted to mitigate… More >

Wei Wang¹, Xinyao Tang^2,*, Kai Zhou¹, Chunhui Zhao¹, Changfa Liu³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1911-1928, 2023, DOI:10.32604/cmc.2023.043233

Abstract Data Matrix (DM) codes have been widely used in industrial production. The reading of DM code usually includes positioning and decoding. Accurate positioning is a prerequisite for successful decoding. Traditional image processing methods have poor adaptability to pollution and complex backgrounds. Although deep learning-based methods can automatically extract features, the bounding boxes cannot entirely fit the contour of the code. Further image processing methods are required for precise positioning, which will reduce efficiency. Because of the above problems, a CenterNet-based DM code key point detection network is proposed, which can directly obtain the four key points of the DM code.… More >

Mohammed Alarfaj¹, Manahil Waheed², Yazeed Yasin Ghadi³, Tamara al Shloul⁴, Suliman A. Alsuhibany⁵, Ahmad Jalal², Jeongmin Park^6,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1207-1223, 2022, DOI:10.32604/cmc.2022.025671

Abstract Human object interaction (HOI) recognition plays an important role in the designing of surveillance and monitoring systems for healthcare, sports, education, and public areas. It involves localizing the human and object targets and then identifying the interactions between them. However, it is a challenging task that highly depends on the extraction of robust and distinctive features from the targets and the use of fast and efficient classifiers. Hence, the proposed system offers an automated body-parts-based solution for HOI recognition. This system uses RGB (red, green, blue) images as input and segments the desired parts of the images through a segmentation… More >