Classification of food-related places is one of the most recent promising application in the area of scene recognition. It helps to analyze the nutrition intake based on the food-related activity. Lifelogging is used to capture and analyze the data sources to record the events and patterns of a person’s life by using wearable sensors, such as wearable cameras. In visual lifelogging, images are captured by wearing a camera over a long period of time which shows the daily experience of the camera user. We aim to work in the area of food places recognition by analyzing the images, which were captured by the visual lifelogging. In this work, a computer vision based food-related places recognition method will be introduced. Finally, we will develop and implement a fully automated food profiling system by analyzing the image of food-related places. Currently, we used a deep learning based approach for classifying the food-related places, which has shown promising results.