Re-texturing by intrinsic video

In this paper, we present a novel re-texturing approach using intrinsic video. Our approach first indicates the regions of interest by contour-aware layer segmentation. The intrinsic video including reflectance and illumination components within the segmented region is recovered by our weighted energy optimization. We then compute the texture coordinates in key frames and the normals for the re-textured region using the optimization approach we develop. Meanwhile, the texture coordinates in non-key frames are optimized by our energy function. When the target sample texture is specified, the re-textured video is finally created by multiplying the re-textured reflectance component with the original illumination component within the replaced region. As shown in our experimental results, our method can produce high quality video re-texturing results with a variety of sample textures, and also the lighting and shading effects of the original videos are well preserved after re-texturing.