Multiple features fusion based video face tracking

Li, Tianping; Zhou, Pingping; Liu, Hui

doi:10.1007/s11042-019-7414-x

Cited by 8 publications

(3 citation statements)

References 20 publications

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“…In the era of big data, smart campuses will become the future development trend. Just as classes have also changed from offline to online, the outbreak of the epidemic seems to have stimulated the development of the Internet era, and education has gradually integrated with the Internet [25]. e high-end form of the digital campus, the goal and orientation of development, and evolution is a smart campus.…”

Section: Discussionmentioning

confidence: 99%

A Big Data Integration Platform for Ideological and Political Education for Smart Campuses

Gao

et al. 2022

Security and Communication Networks

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The advent of large data and the era of large data has brought significant impact and changes to human production and life. Through the acquisition, analysis, processing, prediction, and dissemination of big data in scientific research, large data has emerged as the source of advanced technological to generate global quantitative data. It not only reveals the gaps and deficiencies of traditional approaches to ideological and mechanical studies methods in obtaining ideological behavior but also information about academic subjects providing support for optimizing and innovative technology and ideological transformation and then conducting intellectual and practical research in colleges and universities. In the age of large digital data, the ideology and politics of education are facing modern domestic and foreign situations, as well as new characteristics and new needs for ideology and politics study. This makes ideology and politics research methods even more important, which is seen as an opportunity for continuous creation and innovation and also adapts to the requirements of the times and reality. Smart campus refers to an intelligent integrated environment for campus work, study, and life based on the Internet of Things. This integrated environment takes various application service systems as the carrier and fully integrates teaching, scientific research, management, and campus life. From the large-scale data era, the educational theory of whether colleges and universities’ ideological and political research is rich or not supports more scientific theories to carry out psychological and mechanical research. It is evident that in the age of large data, the ideological and political research in colleges and institutes is not only a theoretical issue but also an important practical issue. Therefore, conducting ideological and political research in colleges and institutes in the age of large data has profound theoretical significance and great practical significance.

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Section: Discussionmentioning

confidence: 99%

A Big Data Integration Platform for Ideological and Political Education for Smart Campuses

Gao

et al. 2022

Security and Communication Networks

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“…Figure 13 shows the tracking results based on colour features only when a background similar to the face is present. If only colour features are used for PF, the algorithm is insensitive to facial expressions and pose changes, but when an object similar to the face appears in the video, for example, in Frame 82 of Figure 13C, the face is disturbed by the hand, which causes the algorithm to misjudge, and the rectangular box cannot locate the correct face position and tracks the hand 43 . The face can be tracked only when the similar background disappears.…”

Section: Resultsmentioning

confidence: 99%

Multiple feature fusion‐based video face tracking for IoT big data

Liu

Huo

et al. 2021

Int J of Intelligent Sys

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With the advancement of Internet of Things (IoT) and artificial intelligence technologies, and the need for rapid application growth in fields, such as security entrance control and financial business trade, facial information processing has become an important means for achieving identity authentication and information security. However, in the process of acquiring facial feature information, face information is easily affected by factors, such as object occlusion, lighting changes, and similar backgrounds. In this paper, we propose a multifeature fusion algorithm based on integral histograms and a real‐time update tracking particle filtering (PF) module. First, edge features and colour features are extracted, weighting methods are used to weight the colour histogram and edge features to describe facial features, and fusion of colour features and edge features is made adaptive by using fusion coefficients to improve face tracking reliability. Then, the integral histogram is integrated into the PF algorithm to simplify the calculation steps of complex particles and improve operational efficiency. Finally, the tracking window size is adjusted in real‐time according to the change in the average distance from the particle centre to the edge of the current model and the initial model to reduce the drift problem and achieve stable tracking with significant changes in the target dimension. The results show that the algorithm improves video tracking accuracy, simplifies particle operation complexity, improves the speed, and has good anti‐interference ability and robustness compared with extracting a single feature.

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“…As a result of face tracking help security forces to investigate the wrongdoing and crimes. Analysts developed a technique for facial tracking based on autonomy-oriented entities (AOEs), and deep learning concepts [43], SDN algorithm [44][45][46][47] to highlight skin color, and extraction. DATA: (APIDIS, from video, Personal data, Visual Tracker Benchmark, images of the same person).…”

Section: Trackingmentioning

confidence: 99%

A review of human skin detection applications based on image processing

et al. 2021

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In computer science, virtual image processing is the use of a digital computer to manipulate digital images through an algorithm for many applications. To begin with a new research topic, the must trend application that gets many requests to develop should know. Therefore, many applications based on human skin and human life are reviewed in this article, such as detection, classification, blocking, cryptography, identification, localization, steganography, segmentation, tracking, and recognition. In this article, the published articles with the topic of human skin-based image processing are investigated. The international publishers, such as Springer, IEEE, arXiv, and Elsevier are selected. The searching is implemented with the duration criteria of 2015-2019. It noted that human skin detection and recognition are the most repetitive articles with 43% and 28.5%, respectively of the total number of the investigated articles. The usage of human skin models is being widely used in the image processing of various applications.

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Multiple features fusion based video face tracking

Cited by 8 publications

References 20 publications

A Big Data Integration Platform for Ideological and Political Education for Smart Campuses

A Big Data Integration Platform for Ideological and Political Education for Smart Campuses

Multiple feature fusion‐based video face tracking for IoT big data

A review of human skin detection applications based on image processing

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