Title
On the Exploitation of One Class Classification to Distinguish Food Vs Non-Food Images.
Abstract
In the last years automatic food image understanding has become an important research challenge for the society. This is because of the serious impact that food intake has in human life. Food recognition engines, can help the monitoring of the patient diet and his food intake habits. Nevertheless, distinguish among different classes of food is not the first question for assisted dietary monitoring systems. Prior to ask what class of food is depicted in an image, a computer vision system should be able to distinguish between food vs non-food images. In this work we consider one-class classification method to distinguish food vs non-food images. The UNICT-FD889 dataset is used for training purpose, whereas other two datasets of food and non-food images has been downloaded from Flickr to test the method. Taking into account previous works, we used Bag-of-Words representation considering different feature spaces to build the codebook. To give possibility to the community to work on the considered problem, the datasets used in our experiments are made publicly available.
Year
DOI
Venue
2015
10.1007/978-3-319-23222-5_46
Lecture Notes in Computer Science
Keywords
Field
DocType
Food understanding,One class classification,Bag of words
Bag-of-words model,Ask price,One-class classification,Monitoring system,Pattern recognition,Food recognition,Computer science,Artificial intelligence,Codebook
Conference
Volume
ISSN
Citations 
9281
0302-9743
6
PageRank 
References 
Authors
0.44
18
4
Name
Order
Citations
PageRank
Giovanni Maria Farinella141257.13
Dario Allegra25612.89
Filippo Stanco313928.91
Sebastiano Battiato465978.73