Vector Field Manipulations in 3-D Time-varying Flow Data Compression and Image/video Editing

摘要

Both the measurement and simulation of unsteady flow yield huge datasets of time-varying volumetric vector fields. Flow dynamics researchers face the very difficult task of finding, extracting and analyzing important flow features (e.g. vortices, shocks) buried in these massive datasets. An MPEG- like method is developed for the compressed transmission of time-varying 3-D flow datasets that emphasizes on feature preservation. Key frames of the flow motion are compressed using a harmonic analysis of the flow. A novel bi-directional advection model is then used to approximate intermediate frames. Key features like vortical structures and shocks lost in compression are reconstructed during visualization. Our algorithm has a much larger compression rate compared to compressing each frame individually and preserves interesting or important flow features in a large unsteady flow dataset.Textureshop is an image editing system that applies texture onto a surface in a photograph. Shape from shading is used to approximate normal field on the surface. Then texture synthesis is applied on that surface with texture coordinates deformed by the recovered normal field. The result is a texture that follows the undulation of the surface.Rototexture is a normal based video editing system that allows a user to apply a time-coherent texture to a surface depicted in the raw video from a single uncalibrated camera, including the surface texture mapping of a texture image and the surface texture synthesis from a texture swatch.Our system avoids the construction of a 3-D shape model and instead uses the recovered normal field to deform the texture so that it plausibly adheres to the undulations of the depicted surface. The texture mapping method uses the non- linear least-squares optimization of a spring model to control the behavior of the texture image as it is deformed to match the evolving normal field through the video. The texture synthesis method uses a coarse optical flow to advect clusters of pixels corresponding to patches of similarly oriented surface points. These clusters are organized into a minimum advection tree to account for the dynamic visibility of clusters. We take a rather crude approach to normal recovering and optical flow estimation, yet the results are robust and plausible for nearly diffuse surfaces such as faces and t-shirts.Morphing is a common practice in digital photograph editing, but morphing does not replace the detail lost where the image is enlarged. We propose an image editing system that decouples feature position from pixel color generation to achieve a morph that preserves texture detail and orientation near the dragged silhouette, synthesized using the original image as an anisotropic texture. We introduce a new distortion to patch-based texture synthesis that aligns texture features with image features. A dense correspondence field between source and target images generated by the control curves can then guide texture synthesis.