human crowd
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Author(s):  
Limin Ren ◽  
Yu Luo ◽  
Guangpeng Lu ◽  
Moyue Cong ◽  
Xinyu Wang ◽  
...  

Author(s):  
Efstratios Kakaletsis ◽  
Ioannis Mademlis ◽  
Nikos Nikolaidis ◽  
Ioannis Pitas
Keyword(s):  

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Rui Shang ◽  
YongMei Ma ◽  
Farhad Ali ◽  
ChuanShuang Hu ◽  
Shah Nazir ◽  
...  

Crowdsourcing is a task-solving model in which human crowd is hired to solve a particular task. During the crowdsourcing process, the crowd selection is performed in order to select appropriate crowd workers for a specific task; without appropriate selection of crowd workers, the process of crowdsourcing is aimless. The main goal of this paper was to identify the features of crowd in crowdsourcing activity, reasons behind crowd participation in the activity of crowdsourcing, and the existing techniques that were utilized for crowd selection in crowdsourcing. Search strings with corresponding keywords were used to capture relevant studies related to crowdsourcing, and crowd selection was classified under conference papers, journal articles, proceedings, and book chapters. 81 relevant studies are selected from 7 digital data repositories using a search strategy. In crowdsourcing practices, crowd selection was considerably addressed. Nonetheless, it has been noticed that the selection is based only on a single crowd worker attribute such as confidence, past success, efficiency, and experience. For the efficiency and effectiveness of the crowdsourcing operation, crowd selection on multicriteria features is essential.


Author(s):  
Claudia Conte ◽  
Giorgio de Alteriis ◽  
Francesco De Pandi ◽  
Enzo Caputo ◽  
Rosario Schiano Lo Moriello ◽  
...  

Author(s):  
Evania Joycelin Anthony ◽  
Regina Anastasia Kusnadi

Globally around the world in 2010, the number of people of all ages visually impaired is estimated to be 285 million, of whom 39 million are blind according to the study of World Health Organization (Global Data on Visual Impairments, 2010). Visual impairment has a significant impact on individuals’ quality of life, including their ability to work and to develop personal relationships. Almost half (48 %) of the visually impaired feel “moderately” or “completely” cut off from people and things around them (Hakobyan, Lumsden, O’Sullivan, & Bartlett, 2013). We believe that technology has the potential to enhance individuals’ ability to participate fully in societal activities and to live independently. So, in this paper we focused to presents a comprehensive literature review about different algorithms of computer vision for supporting blind/vision impaired people, different devices used and the supported tasks. From the 13 eligible papers, we found positive effects of the use of computer vision for supporting visually impaired people. These effects included: the detection of obstacles, objects, door and text, traffic lights, sign detections and navigation. But the biggest challenge for developers now is to increase the speed of time and improve its accuracy, and we expect the future will have a complete package or solution where blind or vision impaired people will get all the solution together (i.e., map, indoor-outdoor navigation, object recognition, obstacle recognition, person recognition, human crowd behavior, crowd human counting, study/reading, entertainment etc.) in one software and in hand-held devices like android or any handy devices.


2021 ◽  
Author(s):  
Fabien Grzeskowiak ◽  
David Gonon ◽  
Daniel Dugas ◽  
Diego Paez-Granados ◽  
Jen Jen Chung ◽  
...  
Keyword(s):  

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 628
Author(s):  
Faisal Abdullah ◽  
Yazeed Yasin Ghadi ◽  
Munkhjargal Gochoo ◽  
Ahmad Jalal ◽  
Kibum Kim

To prevent disasters and to control and supervise crowds, automated video surveillance has become indispensable. In today’s complex and crowded environments, manual surveillance and monitoring systems are inefficient, labor intensive, and unwieldy. Automated video surveillance systems offer promising solutions, but challenges remain. One of the major challenges is the extraction of true foregrounds of pixels representing humans only. Furthermore, to accurately understand and interpret crowd behavior, human crowd behavior (HCB) systems require robust feature extraction methods, along with powerful and reliable decision-making classifiers. In this paper, we describe our approach to these issues by presenting a novel Particles Force Model for multi-person tracking, a vigorous fusion of global and local descriptors, along with a robust improved entropy classifier for detecting and interpreting crowd behavior. In the proposed model, necessary preprocessing steps are followed by the application of a first distance algorithm for the removal of background clutter; true-foreground elements are then extracted via a Particles Force Model. The detected human forms are then counted by labeling and performing cluster estimation, using a K-nearest neighbors search algorithm. After that, the location of all the human silhouettes is fixed and, using the Jaccard similarity index and normalized cross-correlation as a cost function, multi-person tracking is performed. For HCB detection, we introduced human crowd contour extraction as a global feature and a particles gradient motion (PGD) descriptor, along with geometrical and speeded up robust features (SURF) for local features. After features were extracted, we applied bat optimization for optimal features, which also works as a pre-classifier. Finally, we introduced a robust improved entropy classifier for decision making and automated crowd behavior detection in smart surveillance systems. We evaluated the performance of our proposed system on a publicly available benchmark PETS2009 and UMN dataset. Experimental results show that our system performed better compared to existing well-known state-of-the-art methods by achieving higher accuracy rates. The proposed system can be deployed to great benefit in numerous public places, such as airports, shopping malls, city centers, and train stations to control, supervise, and protect crowds.


Author(s):  
Goran Nikola Radoicic ◽  
Miomir Jovanovic

This paper contributes to the research of rhythmic behavior of a group of people, which, more or less synchronized, moves or jumps on a thin and elastic plate, thus performing a dynamically variable load. The analysis of the rhythmic behaviour of the crowd carried out on the basis of the experimental testing on the special steel test platform. The experiment consisted of sixteen measurements of live force and acceleration of the test platform. The dynamic loads caused by the mass of the human crowd and individuals had different intensities. The measurements of acceleration of the carrying platform were performed in order to estimate how the live human force influences on vibrations of machine structures. This research allows us to gain a picture of how serious the threats are from some human actions on the support structure of machines that are handled when performing works in industry, construction or mining. On the basis of these experiments, the mathematical models of the equivalent excitation forces were developed. The measured accelerations of the test platform tread surface and calculated dynamic coefficients of human force indicate that similar actions can seriously endanger balance of the support structure of some machine, and even, for example, can cause the main girder of the bridge crane to fall out. This and similar experiments allow us to formulate appropriate models of excitation loads by human force, which can then be used in simulation analyses in order to develop future systems of electronic protection of machines structures from adverse events.


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