Paper Info
Title
Shoe Detection Using SSD-MobileNet Architecture
Abstract
Falls are a global health issue that especially affects to the elderly. In our previous research, we used a millimeter wave radar to estimate the position of the feet for fall risk assessment of cane users. Radar sensors have a good accuracy, however, due to its low resolution, it is difficult to know if the radar is really tracking the position of the feet or of any other object. In this research, we present a shoe image detector using SSD-MobileNet architecture that could be used in combination with the radar to accurately track the position of the feet. The results show that the proposed detector could correctly recognize the position of the shoes in an image.
Year
DOI
Venue
2020
10.1109/LifeTech48969.2020.1570618965
2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech)
Keywords
DocType
ISBN
balance analysis,deep learning,edge computing,object detection
Conference
978-1-7281-7064-0
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Ibai Gorordo Fernandez101.01
Chikamune Wada2219.55