Vision-based Scene Recognition for Product Search

Author(s):  
Miho Takayanagi ◽  
Osamu Fukuda ◽  
Nobuhiko Yamaguchi ◽  
Hiroshi Okumura ◽  
Anik Nur Handayani
2000 ◽  
Author(s):  
Jennifer E. Sutton ◽  
William A. Roberts
Keyword(s):  

1999 ◽  
Author(s):  
Michael J. Sinai ◽  
Jason S. McCarley ◽  
William K. Krebs
Keyword(s):  

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1718
Author(s):  
Chien-Hsing Chou ◽  
Yu-Sheng Su ◽  
Che-Ju Hsu ◽  
Kong-Chang Lee ◽  
Ping-Hsuan Han

In this study, we designed a four-dimensional (4D) audiovisual entertainment system called Sense. This system comprises a scene recognition system and hardware modules that provide haptic sensations for users when they watch movies and animations at home. In the scene recognition system, we used Google Cloud Vision to detect common scene elements in a video, such as fire, explosions, wind, and rain, and further determine whether the scene depicts hot weather, rain, or snow. Additionally, for animated videos, we applied deep learning with a single shot multibox detector to detect whether the animated video contained scenes of fire-related objects. The hardware module was designed to provide six types of haptic sensations set as line-symmetry to provide a better user experience. After the system considers the results of object detection via the scene recognition system, the system generates corresponding haptic sensations. The system integrates deep learning, auditory signals, and haptic sensations to provide an enhanced viewing experience.


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