Enhanced computational integral imaging system for partially occluded 3D objects using occlusion removal technique and recursive PCA reconstruction

摘要

In this paper, we propose an enhanced computational integral imaging system by both eliminating the occlusion in the elemental images recorded from the partially occluded 3D object and recovering the entire elemental images of the 3D object. In the proposed system, we first obtain the elemental images for partially occluded object using computational integral imaging system and it is transformed to subimages. Then we eliminate the occlusion within the sub-images by use of an occlusion removal technique. To compensate the removed part from occlusion-removed sub-images, we use a recursive application of PCA reconstruction and error compensation. Finally, we generate the entire elemental images without a loss from the newly reconstructed sub-images and perform the process of object recognition. To show the usefulness of the proposed system, we carry out the computational experiments for face recognition and its results are presented. Our experimental results show that the proposed system might improve the recognition performance dramatically.