A Novel Interactive Object Recognition Approach for Real-Time-Type Video Transmission

Author(s):  
Xiaomeng Wu ◽  
Wenli Zhang ◽  
T. Sadasue ◽  
S. Kamijo ◽  
M. Sakauchi
2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.


2014 ◽  
Author(s):  
Kevin Vincent ◽  
Damien Nguyen ◽  
Brian Walker ◽  
Thomas Lu ◽  
Tien-Hsin Chao

Author(s):  
Ken T. Murata ◽  
Takamichi Mizuhara ◽  
Praphan Pavarangkoon ◽  
Kazunori Yamamoto ◽  
Kazuya Muranaga ◽  
...  

2013 ◽  
Vol 756-759 ◽  
pp. 439-442
Author(s):  
Shang Fu Gong ◽  
Li Gang Wu ◽  
Yan Jun Wang

Video surveillance, convenience and rich information, has been widely used in security, protection, monitoring and other occasions, and has already been one of the most important precautionary measures in commercial, residential and transportation areas. However, considering the massive data transmission needs and higher real-time requirements for video surveillance, a remote video surveillance plan has been put forward on the analysis basis of Microsoft DirectShow and Image Compression. This plan adopts the C/S structure, adapts to the requirements of real-time video transmission, with a better fluency. In addition, the picture clarity satisfies the application requirements.


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