[2A2] [General Session] 2. Machine Learning

[2A2-01] Counting garbage bags from garbage collecting video using deep learning

〇Kazuhiro Mikami¹, Makoto Kawano¹, Yin Chen¹, Jin Nakazawa¹ (1. Keio University)

Keywords:Deep Learning, Object detection, Urban sensing

Reducing garbage generated in our daily life is a key aspect to fulfill a sustainable human society. The lack of an effective method to obtaining information regarding the collected garbage, such as where, when and what kinds of waste are collected, is one of the major obstacles to promoting the garbage reduction in cities. In this research, we propose a system to automatically count the number of garbage bags, by using Convolutional Neural Networks (CNN)-based technology to process the videos of garbage collecting process taken by a camera mounted at the back of garbage trucks. The proposed system is evaluated using the realistic garbage collecting videos of Fujisawa city. The experiment result shows that the proposed method achieves a high recall score of 0.90.