Lujuan Deng, Ruochong Fu^*, Zuhe Li, Boyi Liu, Mengze Xue, Yuhao Cui

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4071-4089, 2024, DOI:10.32604/cmc.2024.048200

Abstract Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different spatial positions and sharing the… More >

Xiao Luo^1,3, Hao Zhu^1,2,*, Zhenli Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2667-2687, 2024, DOI:10.32604/cmc.2024.047988

Abstract Road traffic safety can decrease when drivers drive in a low-visibility environment. The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents. To tackle the challenges posed by the low recognition accuracy and the substantial computational burden associated with current infrared pedestrian-vehicle detection methods, an infrared pedestrian-vehicle detection method A proposal is presented, based on an enhanced version of You Only Look Once version 5 (YOLOv5). First, A head specifically designed for detecting small targets has been integrated into the model to make full… More >

Zhihan Liu¹, Xiang Li¹, Siqi Liu², Wei Li^1,*, Xiangxu Meng¹, Jing Jia³

Computer Systems Science and Engineering, Vol.47, No.1, pp. 937-954, 2023, DOI:10.32604/csse.2023.039417

Abstract The COVID-19 virus is usually spread by small droplets when talking, coughing and sneezing, so maintaining physical distance between people is necessary to slow the spread of the virus. The World Health Organization (WHO) recommends maintaining a social distance of at least six feet. In this paper, we developed a real-time pedestrian social distance risk alert system for COVID-19, which monitors the distance between people in real-time via video streaming and provides risk alerts to the person in charge, thus avoiding the problem of too close social distance between pedestrians in public places. We design a lightweight convolutional neural network… More >

Ali Raza¹, Samia Allaoua Chelloug^2,*, Mohammed Hamad Alatiyyah³, Ahmad Jalal¹, Jeongmin Park⁴

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3275-3289, 2023, DOI:10.32604/cmc.2023.029719

Abstract Pedestrian detection and tracking are vital elements of today’s surveillance systems, which make daily life safe for humans. Thus, human detection and visualization have become essential inventions in the field of computer vision. Hence, developing a surveillance system with multiple object recognition and tracking, especially in low light and night-time, is still challenging. Therefore, we propose a novel system based on machine learning and image processing to provide an efficient surveillance system for pedestrian detection and tracking at night. In particular, we propose a system that tackles a two-fold problem by detecting multiple pedestrians in infrared (IR) images using machine… More >

Chintakindi Balaram Murthy¹, Mohammad Farukh Hashmi¹, Ghulam Muhammad^2,3,*, Salman A. AlQahtani^2,3

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3015-3031, 2021, DOI:10.32604/cmc.2021.018781

Abstract Real-time pedestrian detection is an important task for unmanned driving systems and video surveillance. The existing pedestrian detection methods often work at low speed and also fail to detect smaller and densely distributed pedestrians by losing some of their detection accuracy in such cases. Therefore, the proposed algorithm YOLOv2 (“YOU ONLY LOOK ONCE Version 2”)-based pedestrian detection (referred to as YOLOv2PD) would be more suitable for detecting smaller and densely distributed pedestrians in real-time complex road scenes. The proposed YOLOv2PD algorithm adopts a Multi-layer Feature Fusion (MLFF) strategy, which helps to improve the model’s feature extraction ability. In addition, one… More >

Yunzuo Zhang^*, Kaina Guo, Wei Guo, Jiayu Zhang, Yi Li

Journal of Cyber Security, Vol.3, No.2, pp. 79-88, 2021, DOI:10.32604/jcs.2021.017082

Abstract In recent years, pedestrian detection is a hot research topic in the field of computer vision and artificial intelligence, it is widely used in the field of security and pedestrian analysis. However, due to a large amount of calculation in the traditional pedestrian detection technology, the speed of many systems for pedestrian recognition is very limited. But in some restricted areas, such as construction hazardous areas, real-time detection of pedestrians and cross-border behaviors is required. To more conveniently and efficiently detect whether there are pedestrians in the restricted area and cross-border behavior, this paper proposes a pedestrian cross-border detection method… More >

Zhiguo Yan, Zheng Xu, Jie Dai

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 123-132, 2018, DOI:10.1080/10798587.2016.1267251

Abstract In the Big-Data era, currently how to automatically realize acquisition, refining and fast retrieval of the target information in a surveillance video has become an urgent demand in the public security video surveillance field. This paper proposes a new gun-dome camera cooperative system, which solves the above problem partly. The system adopts a master-slave static panorama-variable view dualcamera cooperative video-monitoring system. In this dual-camera system the gun camera static camera） with a wide viewing -angle lenses is in charge of the pedestrian detection and the dome camera can maneuver its focus and cradle orientation to get the clear and enlarged… More >

Yanming Wang^{1, 2, 3}, Kebin Jia^{1, 2, 3}, Pengyu Liu^{1, 2, 3, *}

Journal on Artificial Intelligence, Vol.2, No.3, pp. 113-124, 2020, DOI:10.32604/jai.2020.010137

Abstract In recent years, the problem of “Impolite Pedestrian” in front of the zebra crossing has aroused widespread concern from all walks of life. The traffic sector’s governance measures have become more serious. The traditional way of governance is onsite law enforcement, which requires a lot of manpower and material resources and is low efficiency. An enhanced YOLOv3-tiny model is proposed for pedestrians and vehicle detection in traffic monitoring. By modifying the backbone network structure of YOLOv3- tiny model, introducing deep detachable convolution operation, and designing the basic residual block unit of the network, the feature extraction ability of the backbone… More >

P. K. Santhosh^1,*, B. Kaarthick²

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 625-639, 2019, DOI:10.32604/cmc.2019.05161

Abstract Vision-based player recognition is critical in sports applications. Accuracy, efficiency, and Low memory utilization is alluring for ongoing errands, for example, astute communicates and occasion classification. We developed an algorithm that tracks the movements of different players from a video of a basketball game. With their position tracked, we then proceed to map the position of these players onto an image of a basketball court. The purpose of tracking player is to provide the maximum amount of information to basketball coaches and organizations, so that they can better design mechanisms of defence and attack. Overall, our model has a high… More >