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EFFICIENT SEMI-AUTOMATIC TECHNIQUES FOR IMAGE AND VIDEO MORPHING
PhD Thesis Proposal Defence Title: "EFFICIENT SEMI-AUTOMATIC TECHNIQUES FOR IMAGE AND VIDEO MORPHING" by Miss Jing LIAO Abstract: This thesis proposes a new method for creating smooth transitions between images and videos, and the adaptive transition control scheme. The main challenge in achieving good image morphs is to create a map that aligns corresponding image elements. Our aim is to help automate this often tedious task. We compute the map by optimizing the compatibility of corresponding warped image neighborhoods using an adaptation of structural similarity. The optimization is regularized by a thin-plate spline, and may be guided by a few user-drawn points. We parameterize the map over a halfway domain and show that this representation offers many benefits. The map is able to treat the image pair symmetrically, model simple occlusions continuously, span partially overlapping images, and define extrapolated correspondences. Moreover, it enables direct evaluation of the morph in a pixel shader without mesh rasterization. We improve the morphs by optimizing quadratic motion paths and by seamlessly extending content beyond the image boundaries. We parallelize the algorithm on a GPU to achieve a responsive interface and demonstrate challenging morphs obtained with little effort. When extending image morphing to video morphing, it presents added challenges. Because motions are often unsynchronized, temporal alignment is also necessary. Applying morphing to individual frames leads to discontinuities, so temporal coherence must be considered. Our approach is to optimize a full spatiotemporal mapping between the two videos. We reduce tedious interactions by letting the optimization derive the fine-scale map given only sparse userspecified constraints. For robustness, the optimization objective examines structural similarity of the video content. We demonstrate the approach on a variety of videos, obtaining results using few explicit correspondences. We also explore some adaptive transition functions for image and video morphing, and provide users a convenient tool for intuitive control on the transition rates, to produce some more interesting results. Date: Tuesday, 23 September 2014 Time: 12:00noon - 2:00pm Venue: Room 3494 lifts 25/26 Committee Members: Dr. Pedro Sander (Supervisor) Prof. Long Quan (Chairperson) Dr. Huamin Qu Prof. Chiew-Lan Tai **** ALL are Welcome ****