Efficient image retrieval based mobile indoor localization
Vision based localization has been investigated for many years. The existing Structure from Motion (SfM) technique can reconstruct the 3D models based on the input images. The image retrieval and feature matching allow us to find the correspondence between the query image and the 3D model. According to these, the location can be easily calculated. In mobile scenarios, the limited CPU speed, memory storage and network latency bring in new challenges. The state-of-the-art solution can not be easily adopted due to the complicated calculation and large resource consumption. In this paper, we leverage the techniques developed during the MPEG-7 Compact Descriptors for Visual Search (CDVS) standardization, which aims to provide high performance and low complexity compact descriptors. We show that these techniques are suitable for mobile device and can achieve state-of-the-art retrieval performance in indoor environment. Besides, we propose additional components including blur measurement and result smoothing to improve the performance of the location calculation process. Based on these techniques, a whole system which enables fast vision based localization on mobile device is developed. We present experiments on the real world situation, showing that the system can strike a balance between accuracy and efficiency.