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

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 areas around the object. Then… More >

Shabana Habib¹, Noreen Fayyaz Khan^2,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3321-3335, 2021, DOI:10.32604/cmc.2021.015504

Abstract Vehicle type classification is considered a central part of an intelligent traffic system. In recent years, deep learning had a vital role in object detection in many computer vision tasks. To learn high-level deep features and semantics, deep learning offers powerful tools to address problems in traditional architectures of handcrafted feature-extraction techniques. Unlike other algorithms using handcrated visual features, convolutional neural network is able to automatically learn good features of vehicle type classification. This study develops an optimized automatic surveillance and auditing system to detect and classify vehicles of different categories. Transfer learning is used to quickly learn the features… More >

Yunzuo Zhang^1,*, Shasha Zhang¹, Jiayu Zhang¹, Kaina Guo¹, Zhaoquan Cai²

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 259-272, 2021, DOI:10.32604/iasc.2021.017200

Abstract Video key frame extraction, reputed as an essential step in video analysis and content-based video retrieval, and meanwhile, also serves as the basis and premise of generating video synopsis. Video key frame extraction means extracting the meaningful parts of the video by analyzing their content and structure to form a concise and semantically expressive summary. Up to now, people have achieved many research results in key frame extraction. Nevertheless, because the surveillance video has no specific structure, such as news, sports games, and other videos, it is not accurate enough to directly extract the key frame with the existing effective… More >

Ghulfam Zahra¹, Muhammad Imran¹, Abdulrahman M. Qahtani^2,*, Abdulmajeed Alsufyani², Omar Almutiry³, Awais Mahmood³, Fayez Eid Alazemi⁴

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3465-3481, 2021, DOI:10.32604/cmc.2021.017454

Abstract In recent years, video surveillance application played a significant role in our daily lives. Images taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the visibility. The reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery, object detection, target killing, and surveillance. To remove fog and enhance visibility, a number of visibility enhancement algorithms and methods have been proposed in the past. However, these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer… More >

Yunzuo Zhang^1,*, Shasha Zhang¹, Yi Li¹, Jiayu Zhang¹, Zhaoquan Cai², Shui Lam³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4175-4190, 2021, DOI:10.32604/cmc.2021.017011

Abstract With the explosive growth of surveillance video data, browsing videos quickly and effectively has become an urgent problem. Video key frame extraction has received widespread attention as an effective solution. However, accurately capturing the local motion state changes of moving objects in the video is still challenging in key frame extraction. The target center offset can reflect the change of its motion state. This observation proposed a novel key frame extraction method based on moving objects center offset in this paper. The proposed method utilizes the center offset to obtain the global and local motion state information of moving objects,… More >

Abdullah Alharbi^1,*, Wael Alosaimi¹, M. Irfan Uddin²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 303-317, 2021, DOI:10.32604/cmc.2021.016230

Abstract COVID-19 disease is spreading exponentially due to the rapid transmission of the virus between humans. Different countries have tried different solutions to control the spread of the disease, including lockdowns of countries or cities, quarantines, isolation, sanitization, and masks. Patients with symptoms of COVID-19 are tested using medical testing kits; these tests must be conducted by healthcare professionals. However, the testing process is expensive and time-consuming. There is no surveillance system that can be used as surveillance framework to identify regions of infected individuals and determine the rate of spread so that precautions can be taken. This paper introduces a… More >

Yasir Shahzad^1,*, Huma Javed¹, Haleem Farman², Jamil Ahmad², Bilal Jan³, Abdelmohsen A. Nassani⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2463-2480, 2021, DOI:10.32604/cmc.2021.014904

Abstract Smart healthcare integrates an advanced wave of information technology using smart devices to collect health-related medical science data. Such data usually exist in unstructured, noisy, incomplete, and heterogeneous forms. Annotating these limitations remains an open challenge in deep learning to classify health conditions. In this paper, a long short-term memory (LSTM) based health condition prediction framework is proposed to rectify imbalanced and noisy data and transform it into a useful form to predict accurate health conditions. The imbalanced and scarce data is normalized through coding to gain consistency for accurate results using synthetic minority oversampling technique. The proposed model is… More >

Junchuan Yang^*

Journal of New Media, Vol.2, No.4, pp. 137-148, 2020, DOI:10.32604/jnm.2020.014278

Abstract Person Re-identification (re-ID) is a hot research topic in the field of computer vision now, which can be regarded as a sub-problem of image retrieval. The goal of person re-ID is to give a monitoring pedestrian image and retrieve other images of the pedestrian across the device. At present, person re-ID is mainly divided into two categories. One is the traditional methods, which relies heavily on manual features. The other is to use deep learning technology to solve. Because traditional methods mainly rely on manual feature, they cannot adapt well to a complex environment with a large amount of data.… More >

Zhiyong Dai^1,*, Jianjun Yi¹, Yajun Zhang¹, Liang He²

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 887-903, 2020, DOI:10.32604/iasc.2020.010122

Abstract The rapid development of Internet of Things (IoT) technologies has boosted smart energy networks in recent years. However, power line surveillance systems still suffer from the low accuracy and efficiency of the power line area recognition and risk objects detection. This paper proposes a new customized loss function to tackle the disequilibrium of the size of objects on multi-scale feature maps in the deep learning-based detectors. To validate the new concept and improve the efficiency, we also presented a new object detection model. Experimental results are provided to exhibit the advantage of our proposed method in both accuracy and efficiency. More >

Jianhui Wu^1,2, Feng Huang^1,2, Wenjing Hu²,Wei He^1,2, Bing Tu^1,2, Longyuan Guo^1,2, Xianfeng Ou^1,2,*

Computer Systems Science and Engineering, Vol.33, No.5, pp. 327-334, 2018, DOI:10.32604/csse.2018.33.327

Abstract Face detection is very important in video surveillance of public safety. This paper proposed a face detection method based on the best optimization convex grouping to detect the face regions from different face shape images at actual conditions. Firstly, the basic principle of convex grouping was discussed, the main rules of convex and the structure of the convex polygons was described. And then the best optimization convex grouping algorithm of the convex polygons was designed. At last, all of the algorithms, which used the best optimization convex grouping to detect the face region on the data set of MIT single… More >