Panoramic background generation and abnormal behavior detection in PTZ camera networks
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Manifold Modeling and Its Application to Tubular Scene Manifold Mosaicing Algorithm
Journal of Mathematical Imaging and Vision
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This paper presents a gradient domain approach for eliminating ghosting artifacts caused by moving objects in panoramic images. In this approach, an eliminating ghosting operation is integrated into a panorama stitching process. For each source image, we pre-stitch it to the panoramic image and perform ghosting detection in the overlapping area. If a ghosting artifact is found, we locate the corresponding moving object in the source image, apply a gradient domain object removing and region filling operation to remove the moving object, and stitch the image again. In the gradient domain operation, a gradient vector field is created with gradients of the source image. The object region is emptied after the object is removed and filled with the best-fit patches found by the region filling process in the pixel color domain and the gradient domain. The updated gradient vector field is used for constructing a Poisson equation. A modified source image can be recovered from the gradient vector field by solving the Poisson equation with boundary conditions. When all source images are processed, the final panoramic image can be obtained and the ghosting artifacts are eliminated. The approach presents several advantages. Since the eliminating ghosting operation is performed in the gradient domain, it is very easy to integrate it with gradient domain image blending to produce high quality panoramic images. It can be applied to a general ghosting artifact case caused by moving objects. The approach is applied for producing mobile panoramic images and eliminating ghosting artifacts. It presents good performance in applications.