A survey on computer vision based human analysis in the COVID-19 era

Eyiokur, Fevziye Irem; Kantarcı, Alperen; Erakin, Mustafa Ekrem; Damer, Naser; Ofli, Ferda; Imran, Muhammad; Krizaj, Janez; Salah, Albert Ali; Waibel, Alexander; Ekenel, Hazım Kemal

doi:10.1016/j.imavis.2022.104610

Cited by 10 publications

(5 citation statements)

References 134 publications

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“…In [69] was used CV techniques to collaborate with the control and mitigation of the transmission of COVID-19, given the health emergency that hit the world in recent years. The proposed system assesses whether in public areas, for example, preventive measures, such as wearing a mask, social distancing and avoiding touching your mouth, announced by the competent health bodies, are being followed.…”

Section: Computer Visionmentioning

confidence: 99%

Proposal of Simultaneous Localization and Mapping for Mobile Robots Indoor Environments Using Petri Nets and Computer Vision

Mota,

Batista,

Alexandria

2024

Preprint

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Studies in the area of mobile robotics have advanced in recent years, mainly due to the evolution of technology and the growing need for automated and dynamic solutions in sectors such as industry, transport and agriculture. These devices are complex and the ideal method for localizing, mapping and navigating autonomous mobile robots changes depending on the application. Thus, the general objective of this work is to propose a simultaneous localization and mapping method for autonomous mobile robots in indoor environments, using Computer Vision (CV) and Petri Net (PN). A landmark was placed next to each door in the analyzed region and images were acquired as the rooms in the environment were explored. The algorithm processes the images to count and identify the doors. A transition is created in the PN for each door found and the rooms connected by these doors are represented by the places in the PN. Then, one of the doors is crossed, new images are obtained and the process is repeated until all rooms are explored. The algorithm generates an PN, which can be represented by an image file (.png) and a file with the extension .pnml. The results compare the layout of four environments with the respective generated PNs. Furthermore, six evaluation criteria are proposed for validating Petri nets as a topological map of environments. It is concluded that using PN for this purpose presents originality and potential innovation, being a SLAM technique for indoor environments, which demands low computational cost.

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Section: Computer Visionmentioning

confidence: 99%

Proposal of Simultaneous Localization and Mapping for Mobile Robots Indoor Environments Using Petri Nets and Computer Vision

Mota,

Batista,

Alexandria

2024

Preprint

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“…The use of this technology is increasingly gaining popularity in various domains [19], both serving as a research tool and finding applications in the public and private sectors. Examples of computer vision applications include object extraction in photogrammetry [20], medical research [21,22], road tracking using aerial images [23,24], animal ecology [25], early fire detection [26], player tracking and ball tracking in sports [27], and in the building and construction industry [28].…”

Section: Use Of Artificial Intelligence To Improve Quarries Inventoriesmentioning

confidence: 99%

Identification of Aggregates Quarries via Computer Vision Analysis as a Tool for Sustainable Aggregates Management and Land Planning

López-Acevedo,

Herrero,

Escavy

et al. 2024

Sustainability

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The mineral raw materials industry is crucial for European industry, with the European Economic and Social Committee estimating that 70% of the industry relies directly or indirectly on its supply. In the context of a decarbonized and digitalized economy, the new European industrial model requires carbon-neutral raw materials and production processes. The crucial role of aggregates mining, as the primary construction material, emerges as a key supplier in this paradigm. Aggregates are the main component of the built environment and are a social and economic engine in most countries. Quarries of this type include a wide range of sizes and exploitation methods and use characteristic mining and processing equipment. Quarries are commonly close to their processing plants, which transform natural rock into crushed and ground materials with different grain sizes depending on the future uses. The quarry itself and the presence of certain equipment and facilities help distinguish it from mining sites that exploit other materials. Effective management of aggregates quarries is important in promoting circular economy practices, ensuring efficient management, reuse, and recycling of diverse wastes, including the recovery of high-value components and the production of recycled aggregates, and addressing construction and demolition waste (DCW) management. As aggregates become a progressively scarcer resource due to the increasing demand from developing countries, it is essential to provide reliable and comprehensive information on their potential to the public, policymakers, and other stakeholders to promote their use. This study focuses on employing artificial intelligence and computer vision analysis to automatically identify aggregates quarries from satellite images within continental Spain. A model has been trained to detect aggregates quarries from satellite images by computer vision. The model permits the detection of mining exploitation and the objects located at the interior, which permits determination of the type of mine and the activity status of it. The findings highlight the ability of artificial vision to discern quarries and distinguish whether the observed feature is an aggregates quarry. Additionally, the technology allows for the determination of the quarry’s operational status, distinguishing between active and abandoned quarries. The ability to detect the locations of quarries and assess their activity statuses is of significant value for resource exploration initiatives and location-allocation assessments. It can be a valuable tool for authorities involved in land planning, activities monitoring, and early detection of potential illegal mining activities. This analytical approach demonstrates substantial potential for various stakeholders, including mining companies, mining authorities, policymakers, and land use planners in both the private and public sectors.

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“…muncul.Salah satu kegunaan utama computer vision dan teknologi deep learning adalah mengajarkan model computer vision untuk mendeteksi gerakan tangan manusia. Terutama penting di sini, adalah teknik computer vision itu fokus pada analisis orang dan wajah dalam data visual dan paling terpengaruh [10]…”

Section: Melatih Model Computer Vision Untuk Engenali Gerakan Tangan ...unclassified

Gerakan Tangan Pemain Otomatis Menggunakan Computer Vision

Fahrudin,

Andriani,

Muallimin

et al. 2023

jits

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Gesture recognition allows users of computer science technology to connect with their digital devices more conveniently. Technology for gesture recognition can be helpful in a variety of contexts, such as automated household appliances, automobiles, and interpretation of hand gestures. Gesture recognition is part of gesture recognition which determines what message a certain hand movement wants to convey. In developing this automatic hand movement we use segmentation and object detection where this method involves using algorithms to detect and identify objects or areas related to hand movements. , such as human skin, fingers, and others. Detection of human hand movements using computer vision is a digital image processing technique that aims to recognize human hand movements from image or video data. This technique can be applied in various applications such as human-computer interaction, hand gesture recognition, or video games. Making Automatic Player Hand Movements Using Computer Vision has the potential to improve the user experience when playing games or using interactive applications that require hand movements, according to the research and development that has been done. Games could be controlled more precisely and with less need for additional hardware such as joysticks or controllers if computer vision technology was able to accurately distinguish hand movements.

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A survey on computer vision based human analysis in the COVID-19 era

Cited by 10 publications

References 134 publications

Proposal of Simultaneous Localization and Mapping for Mobile Robots Indoor Environments Using Petri Nets and Computer Vision

Proposal of Simultaneous Localization and Mapping for Mobile Robots Indoor Environments Using Petri Nets and Computer Vision

Identification of Aggregates Quarries via Computer Vision Analysis as a Tool for Sustainable Aggregates Management and Land Planning

Gerakan Tangan Pemain Otomatis Menggunakan Computer Vision

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