Background Inpainting for Videos with Dynamic Objects and a Free-Moving Camera

Granados, Miguel; Kim, Kwang In; Tompkin, James; Kautz, Jan; Theobalt, Christian

doi:10.1007/978-3-642-33718-5_49

Cited by 87 publications

(115 citation statements)

References 24 publications

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“…We will start by discussing a relatively easier application to high dynamic range video [58], and then proceed to briefly discuss two works on video inpainting [59,60], followed by video summarization by means of "video tapestries" [61]. The method of Kalantari et al [58] reconstructs high-dynamic range (HDR) video.…”

Section: Videomentioning

confidence: 99%

“…The problem is further complicated because both the camera and foreground objects may move, and introduce parallax, occlusions, disocclusions, and shadows. Granados et al [59] developed a video inpainting method that aligns other candidate frames to the frame that is to be removed, selects among candidate pixels for the inpainting using a color-consistency term, and then removes intensity differences using gradient-domain fusion. Granados et al assumed a piecewise planar background region.…”

Section: Fig 10mentioning

confidence: 99%

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A survey of the state-of-the-art in patch-based synthesis

Barnes

Zhang

2017

Comp. Visual Media

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This paper surveys the state-of-the-art of research in patch-based synthesis. Patch-based methods synthesize output images by copying small regions from exemplar imagery. This line of research originated from an area called "texture synthesis", which focused on creating regular or semi-regular textures from small exemplars. However, more recently, much research has focused on synthesis of larger and more diverse imagery, such as photos, photo collections, videos, and light fields. Additionally, recent research has focused on customizing the synthesis process for particular problem domains, such as synthesizing artistic or decorative brushes, synthesis of rich materials, and synthesis for 3D fabrication. This report investigates recent papers that follow these themes, with a particular emphasis on papers published since 2009, when the last survey in this area was published. This survey can serve as a tutorial for readers who are not yet familiar with these topics, as well as provide comparisons between these papers, and highlight some open problems in this area.

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Section: Videomentioning

confidence: 99%

Section: Fig 10mentioning

confidence: 99%

A survey of the state-of-the-art in patch-based synthesis

Barnes

Zhang

2017

Comp. Visual Media

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“…In Figure 9 we perform a video inpainting task, for which video zones to remove or to keep are selected in only very few clicks. This is to be compared with the state of the art [9] which requires manual segmentation of all frames. Clusters of fibers were computed and selected with only 7 mouse clicks to distinguish the disturbing girl from the reporter and background.…”

Section: Experiments and Complexitymentioning

confidence: 99%

Hierarchical representation of videos with spatio-temporal fibers

Kumar

Charpiat

Thonnat

2014

IEEE Winter Conference on Applications of Computer Vision

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We propose a new representation of videos, as spatiotemporal fibers. These fibers are clusters of trajectories that are meshed spatially in the image domain. They form a hierarchical partition of the video into regions that are coherent in time and space. They can be seen as dense, spatiallyorganized, long-term optical flow. Their robustness to noise and ambiguities is ensured by taking into account the reliability of each source of information.As fibers allow users to handle easily moving objects in videos, they prove useful for video editing, as demonstrated in a video inpainting example.

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“…Granados et al [13] have recently proposed an efficient inpainting method, yielding compelling results even for large holes and high resolution videos. A brief description is given in the following.…”

Section: Introductionmentioning

confidence: 99%

“…To find the best one, a cost function is globally minimized. Such global minimization, which strives to find the best trade-off between different energy terms, significantly improves the space-time consistency [11], [13], [15]. These approaches are unfortunately time consuming even for low resolution sequences.…”

Section: Introductionmentioning

confidence: 99%