التفاصيل البيبلوغرافية
| العنوان: |
Color coded social distance detector. |
| المؤلفون: |
Ushasree, D., Bollina, Devi Sai Tanusha, Donghisharpu, Vinuthna, Manda, Anjali, Devadurgam, Sravani |
| المصدر: |
AIP Conference Proceedings; 2023, Vol. 2754 Issue 1, p1-5, 5p |
| مصطلحات موضوعية: |
COLOR codes, SOCIAL distance, SOCIAL distancing, MEDICAL scientists, EUCLIDEAN distance |
| مستخلص: |
The happening COVID-19 flare-up has caused a worldwide debacle with its dangerous growth. In the battle against the virus, social distancing (SD) has shown to be an extremely successful step to telephone back the growth of the infection. Because of this, medical experts and scientists are urging the population to reduce the physical contact between them to make sure that the odds of contacting the infection is reduced to its lowest without any major effects. To guarantee social distancing in open places and work terrain, we have created social distancing (SD) discovery aid that can check if individualities are staying down from one another by assaying live video courses from mosaic. For the case where people working in the surroundings, product lines, shops can incorporate this software to their surveillance camera fabrics and can screen whether individualities are staying down from one another or not. The system utilizes the YOLOv3 object acknowledgement worldview to fete people in video groupings. Our work identifies people using detected bounding box information. The distancing method used in our work is the Euclidean distance, which makes use of the bottommost centroid point of the detected people's bounding box to calculate the distance between two people. After the distance has been calculated and estimated accurately, we set a threshold after approximating this estimated distance to pixel. The threshold used in calculating the violation of the distance between persons is 6 feet (approx. 180cm). This violation limit is setup to check if the distance between the individuals is within the distance guidelines set by the government. The significant factors of our task are Detect people with the frame YOLOv3, Calculate distance between each mortal linked in the frame and show the number of individualities at high, low and at no danger. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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