Indoor Positioning System Based On Multiple Image Sensors

To meet the growing needs of people for positioning systems, indoor positioning systems have been rapid development. Indoor space is relatively small, so the positioning systems require greater precision than otherwise, positioning method requires the robustness of error is stronger, and indoor positioning devices must be simple. This paper uses multiple image sensors to complete the process of locating, images are collected by image sensors, then these images will be corrected for deformity or other corresponding image processing. Take into account there are more than one image sensor, the sensor planning is essential. It can not only improve accuracy, but also give the optimal position, which is the focus of the study.This paper not only gives a detailed account of camera calibration algorithm and camera model, but also improves an algorithmic of fixing the relative position of multiple image sensors. We analyze questions from the perspective of binocular vision by this algorithm; it only needs one calibration plate between two cameras to determine the relative position. In this paper, we employ the most optimized theory for the sensor planning, and we not only get the camera's optimal location, but also improve accuracy.The difficulty with this paper is that which algorithms should be taken for the solution of problems when employ the most optimized theory. By reading the literature, the genetic algorithm can solve the problem most effectively.