Riad Alharbey¹, Ameen Banjar¹, Yahia Said^2,3,*, Mohamed Atri⁴, Abdulrahman Alshdadi¹, Mohamed Abid⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6275-6291, 2022, DOI:10.32604/cmc.2022.024272 - 14 January 2022

Abstract Hajj and Umrah are two main religious duties for Muslims. To help faithfuls to perform their religious duties comfortably in overcrowded areas, a crowd management system is a must to control the entering and exiting for each place. Since the number of people is very high, an intelligent crowd management system can be developed to reduce human effort and accelerate the management process. In this work, we propose a crowd management process based on detecting, tracking, and counting human faces using Artificial Intelligence techniques. Human detection and counting will be performed to calculate the number… More >

Olubukola D. Adekola^1,*, Onyedikachi Kenny Udekwu², Oluwatobi Tolulope Saliu², Damilola Williams Dada², Stephen O. Maitanmi¹, Victor Odumuyiwa³, Olujimi Alao², Monday Eze², Funmilayo Abibat Kasali⁴, Ayokunle Omotunde²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 875-890, 2022, DOI:10.32604/csse.2022.021029 - 10 November 2021

Abstract The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies… More >

Abdollah Amirkhani^1,*, Amir Hossein Barshooi¹, Amir Ebrahimi²

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 981-997, 2022, DOI:10.32604/cmc.2022.019001 - 07 September 2021

Abstract The performance and accuracy of computer vision systems are affected by noise in different forms. Although numerous solutions and algorithms have been presented for dealing with every type of noise, a comprehensive technique that can cover all the diverse noises and mitigate their damaging effects on the performance and precision of various systems is still missing. In this paper, we have focused on the stability and robustness of one computer vision branch (i.e., visual object tracking). We have demonstrated that, without imposing a heavy computational load on a model or changing its algorithms, the drop in… More >

Dequan Guo¹, Qingshuai Yang², Yu-Dong Zhang³, Gexiang Zhang¹, Ming Zhu¹, Jianying Yuan^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 191-205, 2021, DOI:10.32604/cmes.2021.016347 - 24 August 2021

Abstract Autonomous intelligence plays a significant role in aviation security. Since most aviation accidents occur in the take-off and landing stage, accurate tracking of moving object in airport apron will be a vital approach to ensure the operation of the aircraft safely. In this study, an adaptive object tracking method based on a discriminant is proposed in multi-camera panorama surveillance of large-scale airport apron. Firstly, based on channels of color histogram, the pre-estimated object probability map is employed to reduce searching computation, and the optimization of the disturbance suppression options can make good resistance to similar More >

Wonseok Jung¹, Se-Han Kim², Seng-Phil Hong³, Jeongwook Seo^4,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 337-348, 2021, DOI:10.32604/cmc.2021.014561 - 12 January 2021

Abstract Pig farmers want to have an effective solution for automatically detecting and tracking multiple pigs and alerting their conditions in order to recognize disease risk factors quickly. In this paper, therefore, we propose a novel monitoring system using an Artificial Intelligence of Things (AIoT) technique combining artificial intelligence and Internet of Things (IoT). The proposed system consists of AIoT edge devices and a central monitoring server. First, an AIoT edge device extracts video frame images from a CCTV camera installed in a pig pen by a frame extraction method, detects multiple pigs in the images More >

Yong‐Hwan Lee, Hyochang Ahn, Hyo‐Beom Ahn, Sun‐Young Lee

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 205-215, 2019, DOI:10.31209/2018.100000056

Abstract Object tracking plays an important role in many vision applications. This paper proposes a novel and robust object detection and tracking method to localize and track a visual object in video stream. The proposed method is consisted of three modules; object detection, tracking and learning. Detection module finds and localizes all apparent objects, corrects the tracker if necessary. Tracking module follows the interest object by every frame of sequences. Learning module estimates a detecting error, and updates its value of credibility level. With a validity level where the tracking is failed on tracing the learned More >

Yongxiang Gu¹, Beijing Chen¹, Xu Cheng^1,*, Yifeng Zhang^2,3, Jingang Shi⁴

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 23-33, 2019, DOI:10.32604/jihpp.2019.05938

Abstract Recently, deep learning has achieved great success in visual tracking. The goal of this paper is to review the state-of-the-art tracking methods based on deep learning. First, we categorize the existing deep learning based trackers into three classes according to network structure, network function and network training. For each categorize, we analyze papers in different categories. Then, we conduct extensive experiments to compare the representative methods on the popular OTB-100, TC-128 and VOT2015 benchmarks. Based on our observations. We conclude that: (1) The usage of the convolutional neural network (CNN) model could significantly improve the… More >

Fangming Bi^1,2, Xin Ma^1,2, Wei Chen^1,2,*, Weidong Fang³, Huayi Chen^1,2, Jingru Li^1,2, Biruk Assefa^1,4

Journal of New Media, Vol.1, No.2, pp. 63-74, 2019, DOI:10.32604/jnm.2019.06253

Abstract Video object tracking is an important research topic of computer vision, which finds a wide range of applications in video surveillance, robotics, human-computer interaction and so on. Although many moving object tracking algorithms have been proposed, there are still many difficulties in the actual tracking process, such as illumination change, occlusion, motion blurring, scale change, self-change and so on. Therefore, the development of object tracking technology is still challenging. The emergence of deep learning theory and method provides a new opportunity for the research of object tracking, and it is also the main theoretical framework More >