Food524DB is the largest publicly available food dataset with 524 food classes and 247,636 images by merging food classes from existing datasets in the state of the art. This database can be used for food recognition. The database is composed of 247,636 images belonging to 524 food categories.
In this project we present a method for logo recognition based on deep learning. Our recognition …
Automatic food recognition is an important task to support the users in their daily dietary monitoring and to keep tracks of their food consumption. We have designed datasets and algorithms for automatic dietary monitoring of canteen customers based on robust computer vision techniques.
A review of existing methods for local visual detectors and descriptors.
We have developed the iVAT: an interactive Video Annotation Tool. It supports manual, semi-automatic and automatic annotations through the interaction of the user with various detection algorithms.