Locating objects in spherical panoramic images

In this paper, a method for locating objects in spherical panorama is proposed. Given a set of reference images for reference stored in the database and a query image, we would find the nearest image in the database, and then label the corresponding location on the spherical panorama. Since there are differences between spherical panoramic image and query view which is mostly captured by normal camera, the traditional methods could not be used to solve this problem directly. Therefore, we transform the query image into parts of spherical panorama, and derive the essential matrix and homograph matrix in spherical panoramic image based on the property of spherical panorama. We adopt SIFT to detect the features in spherical panorama, and then reject the wrong matching points using RANSAC according to the essential matrix we derived. The remaining matching feature points are still more than others in spherical panorama database. We calculate the homograph matrix, and then the corresponding position in spherical panoramic image will be detected. The experiments verify the validity of the method proposed in this paper.