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We propose a digital video stabilization process using information that the scale-invariant feature transform (SIFT) provides for each frame. We use a fuzzy clustering scheme to separate the SIFT features representing global motion from those representing local motion. We then calculate the global orientation change and translation between the current frame and the previous frame. Each frame's translation...
We propose a digital video stabilization process using information that the scale-invariant feature transform (SIFT) provides for each frame. We use a fuzzy clustering scheme to separate the SIFT features representing global motion from those representing local motion. We then calculate the global orientation change and translation between the current frame and the previous frame. Each frame's translation...
This paper presents a novel framework for recognition of facial action unit (AU) combinations by viewing the classification as a sparse representation problem. Based on this framework, we represent a facial image exhibiting the combination of AUs as a sparse linear combination of basis constituting an overcomplete dictionary. We build an overcomplete dictionary whose main elements are mean Gabor features...
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