Recognition of Tourist Attractions

With the mass of images we are presented with everyday, there are many times when we see a photo of a place that we would like to visit but are unable to determine where it is. The ability to recognize landmarks from images can be extremely useful both when choosing a travel destination and when trying to identify landmarks in a foreign place. Our project aims to be able to recognize the specific location using machine learning methods. Due to time and complexity constraints, we limit ourselves to recognizing ten famous tourist attractions in Beijing. The input to our algorithm is an image. We then use a convolutional neural network to extract image features and an SVM which outputs the predicted attraction. We use the following ten attractions in our model: Tiananmen Square, the Forbidden City, Yuanmingyuan Park, Beihai Park, Beijing National Stadium (Bird Nest), Beijing National Aquatics Centre (Water Cube), CCTV Headquarters, the Great Wall, National Centre for the Performing Arts (Bird Egg) and Fragrant Hills Park. These attractions were chosen because they each have distinct features that make the classification task easier and are well known enough to amass a large dataset for training.