Abstract: A wide spread adoption of 3D videos and technologies is hindered by the lack of high-quality 3D content. One promising solution to address this problem is to use automated 2D-to-3D conversion. However, current conversion methods, while general, produce low-quality results with artefacts that are not acceptable to many viewers. Creating a database of 3D stereoscopic videos with accurate depth is, however, very difficult. Computer generated content can be used to generate high-quality 3D video reference database for 2D-to-3D conversion. The method transfers depth information from frames in the 3D reference database to the target frame while respecting object boundaries. It computes depth maps from the depth gradients, and outputs a stereoscopic video.

Abstract: A wide spread adoption of 3D videos and technologies is hindered by the lack of high-quality 3D content. One promising solution to address this problem is to use automated 2D-to-3D conversion. However, current conversion methods, while general, produce low-quality results with artefacts that are not acceptable to many viewers. Creating a database of 3D stereoscopic videos with accurate depth is, however, very difficult. Computer generated content can be used to generate high-quality 3D video reference database for 2D-to-3D conversion. The method transfers depth information from frames in the 3D reference database to the target frame while respecting object boundaries. It computes depth maps from the depth gradients, and outputs a stereoscopic video.

Abstract: A wide spread adoption of 3D videos and technologies is hindered by the lack of high-quality 3D content. One promising solution to address this problem is to use automated 2D-to-3D conversion. However, current conversion methods, while general, produce low-quality results with artefacts that are not acceptable to many viewers. Creating a database of 3D stereoscopic videos with accurate depth is, however, very difficult. Computer generated content can be used to generate high-quality 3D video reference database for 2D-to-3D conversion. The method transfers depth information from frames in the 3D reference database to the target frame while respecting object boundaries. It computes depth maps from the depth gradients, and outputs a stereoscopic video.

Abstract: The method for dynamic video magnification magnifies small motions occurring simultaneously within large motions. The method involves selecting a region of interest from a video for magnification. The region of interest is warped to obtain a stabilized sequence of frames that discounts large motions. Each frame of the stabilized sequence is decomposed to a foreground layer, a background layer, and an alpha matte layer, and each of the foreground and alpha matte layers is magnified. Then a magnified sequence is generated from the magnified layers using matte inversion. Any image holes in the magnified sequence are filled in using texture synthesis. Finally, the magnified sequence is de-warped to the original space-time coordinates.

Abstract: The method for dynamic video magnification magnifies small motions occurring simultaneously within large motions. The method involves selecting a region of interest from a video for magnification. The region of interest is warped to obtain a stabilized sequence of frames that discounts large motions. Each frame of the stabilized sequence is decomposed to a foreground layer, a background layer, and an alpha matte layer, and each of the foreground and alpha matte layers is magnified. Then a magnified sequence is generated from the magnified layers using matte inversion. Any image holes in the magnified sequence are filled in using texture synthesis. Finally, the magnified sequence is de-warped to the original space-time coordinates.

Abstract: A wide spread adoption of 3D videos and technologies is hindered by the lack of high-quality 3D content. One promising solution to address this problem is to use automated 2D-to-3D conversion. However, current conversion methods, while general, produce low-quality results with artefacts that are not acceptable to many viewers. Creating a database of 3D stereoscopic videos with accurate depth is, however, very difficult. Computer generated content can be used to generate high-quality 3D video reference database for 2D-to-3D conversion. The method transfers depth information from frames in the 3D reference database to the target frame while respecting object boundaries. It computes depth maps from the depth gradients, and outputs a stereoscopic video.