Abstract
This paper presents a parallax-robust video stitching technique for timely synchronized surveillance video. An efficient two-stage video stitching procedure is proposed in this paper to build wide Field-of-View (FOV) videos for surveillance applications. In the stitching model calculation stage, we develop a layered warping algorithm to align the background scenes, which is location-dependent and turned out to be more robust to parallax than the traditional global projective warping methods. On the selective seam updating stage, we propose a change-detection based optimal seam selection approach to avert ghosting and artifacts caused by moving foregrounds. Experimental results demonstrate that our procedure can efficiently stitch multi-view videos into a wide FOV video output without ghosting and noticeable seams.
Highlights
Image stitching, called image mosaicing or panorama stitching, has received a great deal of attention in computer vision [1,2,3,4,5,6,7,8]
We present an efficient parallax-robust surveillance video stitching procedure that combines layered warping and the change-detection based seam updating approach
Inspired by dual homography warp (DHW) [6], we propose to use a layered warping algorithm to align the background scenes, which is location-dependent and turned out to be more robust to parallax than the traditional global projective warping methods and more flexible than DHW [6] which can only process images with two planes
Summary
Called image mosaicing or panorama stitching, has received a great deal of attention in computer vision [1,2,3,4,5,6,7,8]. There are many research works on image stitching [1,2,3,4,5,6,7,8], and it is typically solved by estimating a global 2D projective warp to align the input images. A 2D projective warp uses a homography parameterized by 3 × 3 matrices [1,2,3,9], which can preserve global image structures, but cannot handle parallax. It is correct only if the scene is planar or if the views differ purely by rotation. Due to complex computation and low resolution, they may not be suitable for surveillance application
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