Changyu Liu¹, Hao Huang¹, Guogang Huang^2,*, Chunyin Wu¹, Yingqi Liang³

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4219-4242, 2024, DOI:10.32604/cmc.2024.053625 - 12 September 2024

Abstract Laboratory safety is a critical area of broad societal concern, particularly in the detection of abnormal actions. To enhance the efficiency and accuracy of detecting such actions, this paper introduces a novel method called TubeRAPT (Tubelet Transformer based on Adapter and Prefix Training Module). This method primarily comprises three key components: the TubeR network, an adaptive clustering attention mechanism, and a prefix training module. These components work in synergy to address the challenge of knowledge preservation in models pre-trained on large datasets while maintaining training efficiency. The TubeR network serves as the backbone for spatio-temporal… More >

Yong Li^1,4, Qiming Liang^2,*, Bo Gan³, Xiaolong Cui⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1-23, 2023, DOI:10.32604/cmc.2023.042494 - 31 October 2023

Abstract Action recognition and detection is an important research topic in computer vision, which can be divided into action recognition and action detection. At present, the distinction between action recognition and action detection is not clear, and the relevant reviews are not comprehensive. Thus, this paper summarized the action recognition and detection methods and datasets based on deep learning to accurately present the research status in this field. Firstly, according to the way that temporal and spatial features are extracted from the model, the commonly used models of action recognition are divided into the two stream… 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 - 28 December 2022

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… More >

Khalid A. AlShalfan¹, Mohammed Zakariah^2,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 689-704, 2021, DOI:10.32604/cmc.2021.015989 - 22 March 2021

Abstract Currently, distracted driving is among the most important causes of traffic accidents. Consequently, intelligent vehicle driving systems have become increasingly important. Recently, interest in driver-assistance systems that detect driver actions and help them drive safely has increased. In these studies, although some distinct data types, such as the physical conditions of the driver, audio and visual features, and vehicle information, are used, the primary data source is images of the driver that include the face, arms, and hands taken with a camera inside the car. In this study, an architecture based on a convolution neural More >