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Food Nutrition Visualization on Google Glass: Design Tradeoff and Field…
Food Nutrition Visualization on Google Glass: Design Tradeoff and Field Evaluation
Aim
Augmented reality
aid in nutrtion choice
give real-time nutrient data
technology
RIS
Reverse Image Search
text mining
object tracking
Recognition process
Recognition
CBIR
content based image retrieval
implementation
RIS
capture image
upload to Google # server
feature extraction
global\local features
color
points
lines
textures
SIFT
Text Minning
blacklist
forbidden words
filter out
remaining
frequently accurring words
whitelist
expected words
more specific
match with blacklist
#
nutrient data retrieval
USDA
image tracking and visualizatioin
reduce redundancy
RIS processing
each frame
tracking
descriptors
ORB
Rotated BRIEF
Oriented FAST
LDB
Local Difference Binary
Opombe
Uporabi sliko
augmented reality
scanner
Results
dataset
FIDS30
87.9%
10 Food items in stores
75.9%