Naturalness of warping is gaining extensive attention in image stitching. Recent warps such as SPHP, AANAP and GSP, use a global similarity to effectively mitigate projective distortion (which enlarges regions), however, they necessarily bring in perspective distortion (which generates inconsistency). In this paper, we propose a quasi-homography warp, which balances perspective distortion against projective distortion in the non-overlapping region, to create natural-looking mosaics. Our approach formulates the warp as a solution of a system of bivariate equations, where perspective distortion and projective distortion are characterized as slope preservation and scale linearization respectively. Our proposed warp only relies on a global homography thus is totally parameter-free. A comprehensive experiment shows that quasi-homography outperforms some state-of-the-art warps in urban scenes, including homography, AutoStitch and SPHP. A user study demonstrates that quasi-homography wins most users' favor as well, comparing to homography and SPHP.
Many efforts have been devoted to mitigate distortion in the non-overlapping region for creating a natural-looking mosaic. A pioneering work @cite_28 uses spherical or cylindrical warps to produce multi-perspective results to address this problem, but it necessarily curves straight lines.
@cite_28
1963246386 2059729733 1983683849 2091685917
The goal of image stitching is to create natural-looking mosaics free of artifacts that may occur due to relative camera motion, illumination changes, and optical aberrations. In this paper, we propose a novel stitching method, that uses a smooth stitching field over the entire target image, while accounting for all the local transformation variations. Computing the warp is fully automated and uses a combination of local homography and global similarity transformations, both of which are estimated with respect to the target. We mitigate the perspective distortion in the non-overlapping regions by linearizing the homography and slowly changing it to the global similarity. The proposed method is easily generalized to multiple images, and allows one to automatically obtain the best perspective in the panorama. It is also more robust to parameter selection, and hence more automated compared with state-of-the-art methods. The benefits of the proposed approach are demonstrated using a variety of challenging cases. This paper describes a method to construct seamless image mosaics of a panoramic scene containing two predominate planes: a distant back plane and a ground plane that sweeps out from the camera's location. While this type of panorama can be stitched when the camera is carefully rotated about its optical center, such ideal scene capture is hard to perform correctly. Existing techniques use a single homography per image to perform alignment followed by seam cutting or image blending to hide inevitable alignments artifacts. In this paper, we demonstrate how to use two homographies per image to produce a more seamless image. Specifically, our approach blends the homographies in the alignment procedure to perform a nonlinear warping. Once the images are geometrically stitched, they are further processed to blend seams and reduce curvilinear visual artifacts due to the nonlinear warping. As demonstrated in our paper, our procedure is able to produce results for this type of scene where current state-of-the-art techniques fail. This paper proposes a novel parametric warp which is a spatial combination of a projective transformation and a similarity transformation. Given the projective transformation relating two input images, based on an analysis of the projective transformation, our method smoothly extrapolates the projective transformation of the overlapping regions into the non-overlapping regions and the resultant warp gradually changes from projective to similarity across the image. The proposed warp has the strengths of both projective and similarity warps. It provides good alignment accuracy as projective warps while preserving the perspective of individual image as similarity warps. It can also be combined with more advanced local-warp-based alignment methods such as the as-projective-as-possible warp for better alignment accuracy. With the proposed warp, the field of view can be extended by stitching images with less projective distortion (stretched shapes and enlarged sizes). An image based system and process for rendering novel views of a real or synthesized 3D scene based on a series of concentric mosaics depicting the scene. In one embodiment, each concentric mosaic represents a collection of consecutive slit images of the surrounding 3D scene taken from a different viewpoint tangent to a circle on a plane within the scene. Novel views from viewpoints within circular regions of the aforementioned circle plane defined by the concentric mosaics are rendered using these concentric mosaics. Specifically, a slit image can be identified by a ray originating at its viewpoint on the circle plane and extending toward the longitudinal midline of the slit image. Each of the rays associated with the slit images needed to construct a novel view will either coincide with one of the rays associated with a previously captured slit image, or it will pass between two of the concentric circles on the circle plane. If it coincides, then the previously captured slit image associated with the coinciding ray can be used directly to construct part of the novel view. If the ray passes between two of the concentric circles of the plane, then the needed slit image is interpolated using the two previously captured slit images associated with the rays originating from the adjacent concentric circles that are parallel to the non-coinciding ray. If the objects in the 3D scene are close to the camera, depth correction is applied to reduce image distortion for pixels located above and below the circle plane. In another embodiment, a single camera is used to capture a sequence of images. Each image includes image data that has a ray direction associated therewith. To render an image at a novel viewpoint, multiple ray directions from the novel viewpoint are chosen. Image data is combined from the sequence of images by selecting image data that has a ray direction substantially aligning with the ray direction from the novel viewpoint.