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 >

Yazeed Yasin Ghadi¹, Nida Khalid², Suliman A. Alsuhibany³, Tamara al Shloul⁴, Ahmad Jalal², Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2597-2615, 2022, DOI:10.32604/cmc.2022.024422

Abstract Human Activity Recognition (HAR) plays an important role in life care and health monitoring since it involves examining various activities of patients at homes, hospitals, or offices. Hence, the proposed system integrates Human-Human Interaction (HHI) and Human-Object Interaction (HOI) recognition to provide in-depth monitoring of the daily routine of patients. We propose a robust system comprising both RGB (red, green, blue) and depth information. In particular, humans in HHI datasets are segmented via connected components analysis and skin detection while the human and object in HOI datasets are segmented via saliency map. To track the movement of humans, we proposed… More >