Tao Liu

TL;DR: In this article, an indoor live-action navigation method and system is presented, which consists of the steps that a mobile terminal collects live action images of the current position, the live action image is matched with a first live action view stored in an indoor image database, and an initial coordinate of the position is obtained; the position of a pedestrian is positioned and tracked in real time through a multi-source sensor fused position algorithm, and when the mobile terminal detects that the user changes, a real-time position result and a walking trajectory are output.

TL;DR: This approach decreases the accumulative localization error of PDR by matching the detected structure landmarks to the ground-truth values and is robust to the random turning activities of people and can realize indoor localization with a faster convergence speed.

TL;DR: A visual-based approach is proposed for the construction of a radio map in anonymous indoor environments that can greatly reduce the human labor cost, which increases the potential for applying it to large indoor environments.

TL;DR: In this article, an intelligent mobile terminal constructs an indoor road network model and generates a collecting optimal path, and the intelligent mobile device collects sensor data during user's walking along the path and detects user's stride and identification turning; a dead reckoning method is used to perform position labeling, and position labeling results are corrected through video image data collected by a camera.

TL;DR: In this article, an image processing-based indoor positioning method and system is proposed, which comprises the following steps that: an indoor plane graph is obtained in advance, and reference points are established, position coordinate calculation is calculated for each reference point, and image feature data at the reference points were sampled and are stored; inertial sensor data of a mobile terminal are recorded in real-time, and when it is detected that the mobile terminal photographs a current position image and transmits a positioning request, the image features data are extracted and are transmitted to a server, the server estimates