Highly automated image recomposition : The picture you wish you had taken Have you ever lamented, I wish I had taken a different picture of that u0027Kodak Momentu0027 when everyone was smiling and no one blinked? With image recomposition, we strive to deliver the oneclick fix experience to customers so they can easily create the perfect pictures that they never actually took. To accomplish this, a graphic user interface was created that integrates existing and new algorithms, including face detection, facial feature location, face recognition, expression recognition, face appearance and pose matching, and seamless blending. Advanced modes include face relighting. This system is capable of performing image recomposition from a mixture of videos and still photos, with ease of use and a high degree of automation.

Multiexposure photomontage with handheld cameras Abstract   The paper studies the image fusion from multiple images taken by handheld cameras with different exposures. Existing methods often generate unsatisfactory results, such as blurringghosting artifacts due to the problematic handling of camera motions, dynamic contents, and inappropriately fusion of local regions (e.g., over or under exposed). In addition, they often require a highquality image registration, which is hard to achieve in scenarios with large depth variations and dynamic textures, and is also timeconsuming. In this paper, we propose to enable a rough registration by a single homography and combine the inputs seamlessly to hide any possible misalignment. Specifically, the method first uses a Markov Random Field (MRF) energy for the labeling of all pixels, which assigns different labels to different aligned input images. During the labeling, it chooses wellexposured regions and skips moving objects at the same time. Then, the proposed method combines a Laplacian image according to the labels and constructs the fusion result by solving the Poisson equation. Furthermore, it adds some internal constraints when solving the Poisson equation for balancing and improving fusion results. We present various challenging examples, including staticdynamic, indooroutdoor and daytimenighttime scenes, to demonstrate the effectiveness and practicability of the proposed method.