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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 ****