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JBE, vol. 25, no. 5, pp.685-697, September, 2020


Parallax Distortion Detection and Correction Method for Video Stitching by using LDPM Image Assessment

Seongbae Rhee, Jeonho Kang, and Kyuheon Kim

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Immersive media videos, such as panorama and 360-degree videos, must provide a sense of realism as if the user visited the space in the video, so they should be able to represent the reality of the real world. However, in panorama and 360-degree videos, objects appear to overlap or disappear due to parallax between cameras, and such parallax distortion may interfere with immersion of the user's content. Accordingly, although many video stitching algorithms have been proposed to overcome parallax distortion, parallax distortion still occurs due to the low performance of the Object detection module and limitations of the Seam generation method. Therefore, this paper analyzes the limitations of the existing video stitching technology and proposes a method for detecting and correcting parallax distortion of video stitching using the LDPM (Local Differential Pixel Mean) image evaluation method that overcomes the limitations of the video stitching technique.

Keyword: Video Stitching, Parallax Distortion, Seam Optimization, LDPM, Blending

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