scholarly journals Examining a display-peeping prevention method that uses real-time UI part transparency linked to motion detection by video analysis

2021 ◽  
Vol 10 (3) ◽  
pp. 1546-1557
Author(s):  
Koki Kishibata ◽  
Masaki Narita
Keyword(s):  
User Interface ◽  
Real Time ◽  
Video Analysis ◽  
Motion Detection ◽  
Ease Of Use ◽  
Equivalent Function ◽  
Low Load ◽  
Experimental Subjects ◽  
Prevention Method ◽  
Motion Video

In recent years, the use of various information terminals such as smartphones and personal computers have become widespread, and situations where information terminals are used have become diverse. With increased opportunities to use information terminals outdoors and during travel, some users have been using peep-prevention filters, or software with an equivalent function, on their displays, in order to protect their privacy. However, such filters have problems with regards their effectiveness, ease of use, and the user being able recognize when they are vulnerable to peeping. Decrease in display visibility, unprotected angles, and the fact that it is difficult for users to notice when others are watching their screen, are some examples of such problems. Also, recently, many information terminals recently distributed have built-in cameras. In this paper, in order to solve the aforementioned problems, we propose to detect motion, video analyze , and transparentize part of the user interface (UI) in real time by using a laptop’s built-in camera. This method is enabled with low-load and can be applied to various terminals. Further, in order to verify the effectiveness of the method, we implemented a prototype, and carried out an evaluation experiment on experimental subjects. Results from the experiment confirmed that real-time UI transparentization is a very effective method for protecting privacy of information terminals.

scholarly journals Detection and Adaptive Video Processing of Hyperopia Scene in Sports Video

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qingjie Chen ◽  
Minkai Dong
Keyword(s):  
Real Time ◽  
Target Detection ◽  
Motion Detection ◽  
Difference Method ◽  
Detection Algorithm ◽  
Moving Target ◽  
Target Area ◽  
Moving Target Detection ◽  
Target Extraction ◽  
Motion Video

In the research of motion video, the existing target detection methods are susceptible to changes in the motion video scene and cannot accurately detect the motion state of the target. Moving target detection technology is an important branch of computer vision technology. Its function is to implement real-time monitoring, real-time video capture, and detection of objects in the target area and store information that users are interested in as an important basis for exercise. This article focuses on how to efficiently perform motion detection on real-time video. By introducing the mathematical model of image processing, the traditional motion detection algorithm is improved and the improved motion detection algorithm is implemented in the system. This article combines the advantages of the widely used frame difference method, target detection algorithm, and background difference method and introduces the moving object detection method combining these two algorithms. When using Gaussian mixture model for modeling, improve the parts with differences, and keep the unmatched Gaussian distribution so that the modeling effect is similar to the actual background; the binary image is obtained through the difference between frames and the threshold, and the motion change domain is extracted through mathematical morphological filtering, and finally, the moving target is detected. The experiment proved the following: when there are more motion states, the recall rate is slightly better than that of the VIBE algorithm. It decreased about 0.05 or so, but the relative accuracy rate increased by about 0.12, and the increase ratio is significantly higher than the decrease ratio. Departments need to adopt effective target extraction methods. In order to improve the accuracy of moving target detection, this paper studies the method of background model establishment and target extraction and proposes its own improvement.

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

2015 ◽  
Author(s):  
Jutta Hild ◽  
Wolfgang Krüger ◽  
Stefan Brüstle ◽  
Patrick Trantelle ◽  
Gabriel Unmüssig ◽  
...  
Keyword(s):  
Real Time ◽  
Video Analysis ◽  
Human Observer ◽  
Time Motion ◽  
Motion Video

Real-time Worker Safety Management System Using Deep Learning-based Video Analysis Algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 25-30
Author(s):  
So Yeon Jeon ◽  
Jong Hwa Park ◽  
Sang Byung Youn ◽  
Young Soo Kim ◽  
Yong Sung Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Video Analysis ◽  
Management System ◽  
Safety Management ◽  
Worker Safety ◽  
Safety Management System ◽  
Analysis Algorithm

scholarly journals An Augmented Warning System for Pedestrians: User Interface Design and Algorithm Development

2021 ◽  
Vol 11 (16) ◽  
pp. 7197
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Shan Bao
Keyword(s):  
User Interface ◽  
Real Time ◽  
Interface Design ◽  
Situational Awareness ◽  
Warning System ◽  
User Interface Design ◽  
Warning Systems ◽  
Projection Algorithms ◽  
Time Projection ◽  
Timely Warning

Warning pedestrians of oncoming vehicles is critical to improving pedestrian safety. Due to the limitations of a pedestrian’s carrying capacity, it is crucial to find an effective solution to provide warnings to pedestrians in real-time. Limited numbers of studies focused on warning pedestrians of oncoming vehicles. Few studies focused on developing visual warning systems for pedestrians through wearable devices. In this study, various real-time projection algorithms were developed to provide accurate warning information in a timely way. A pilot study was completed to test the algorithm and the user interface design. The projection algorithms can update the warning information and correctly fit it into an easy-to-understand interface. By using this system, timely warning information can be sent to those pedestrians who have lower situational awareness or obstructed view to protect them from potential collisions. It can work well when the sightline is blocked by obstructions.

scholarly journals Near real time ETEM streaming video analysis

2017 ◽  
Author(s):  
Yuewei Lin ◽  
Dmitri Zakharov ◽  
Remi Megret ◽  
Shinjae Yoo ◽  
Eric Stach
Keyword(s):  
Real Time ◽  
Video Analysis ◽  
Streaming Video
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