Investigating image stitching for action recognition

Li, Yufeng; Li, Ping-An; Lei, Daozhong; Shi, Yuxin; Tan, Lixin

doi:10.1007/s11042-017-5072-4

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…Future works include generalizing quasi-homography warps into spatially-varying warping frameworks like in [26], [27] to improve alignment qualities as well in the overlapping region, and incorporating our method in SPHP to create more naturallooking multi-perspective panoramas. Multimedia applications that are relevant to image stitching could also be considered, such as feature selection [40], video composition [41], crossmedia stitching [42] and action recognition [43].…”

Section: Discussionmentioning

confidence: 99%

Quasi-Homography Warps in Image Stitching

Wang

2018

IEEE Trans. Multimedia

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The naturalness of warps is gaining extensive attentions in image stitching. Recent warps such as SPHP and AANAP, use global similarity warps to mitigate projective distortion (which enlarges regions), however, they necessarily bring in perspective distortion (which generates inconsistencies). In this paper, we propose a novel quasi-homography warp, which effectively balances the perspective distortion against the projective distortion in the non-overlapping region to create a more natural-looking panorama. Our approach formulates the warp as the solution of a bivariate system, where perspective distortion and projective distortion are characterized as slope preservation and scale linearization respectively. Because our proposed warp only relies on a global homography, thus it is totally parameter-free. A comprehensive experiment shows that a quasi-homography warp outperforms some state-of-the-art warps in urban scenes, including homography, AutoStitch and SPHP. A user study demonstrates that it wins most users' favor, comparing to homography and SPHP.

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