# Recognition of Multiple Food Items in a Single Photo for Use in a Buffet-Style Restaurant

## TL;DR

This paper presents a method for recognizing multiple food items in a single image tailored for buffet restaurants, addressing challenges like menu variability and limited training data per class.

## Contribution

It introduces a hierarchical recognition approach combined with food area detection, specifically designed for buffet-style restaurant images with few training samples.

## Key findings

- Hierarchical recognition improves accuracy over baseline methods.
- Food area detection effectively isolates multiple items in complex images.
- The method adapts well to menu changes with limited data.

## Abstract

We investigate image recognition of multiple food items in a single photo, focusing on a buffet restaurant application, where menu changes at every meal, and only a few images per class are available. After detecting food areas, we perform hierarchical recognition. We evaluate our results, comparing to two baseline methods.