Authors:
Hiroki Urakawa
;
Kitahiro Kaneda
and
Keiichi Iwamura
Affiliation:
Tokyo University of Science 6-3-1 Niijuku, katusika-ku Tokyo, 125-8585, Japan
Keyword(s):
Data Hiding, Surveillance Camera, Deep Learning, Artificial Fiber Pattern, Object Detection, Image Reconstruction.
Abstract:
Owing to the low equipment cost, the number of surveillance cameras installed has increased significantly; however, most of them are not being used effectively. These cameras can be used for various purposes, such as marketing, if behavior tracking is possible from the obtained images. Previously, we proposed a method of tracking by embedding information in “Artificial Fiber Pattern.” However, the body shape of the wearer and wrinkles of the clothes affect the accuracy of the results. To overcome this drawback, in this study, we combined PIFu HD, a technology that generates a full three-dimensional model from a single image of a person, with the modeling and calculation of the body shape of the subject to verify the conditions under which the body shape of the wearer and wrinkles in the clothes affect the accuracy. Consequently, we achieved precision improvement by removing data that met unsuitable conditions.