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Randomface : test image; : sparse indicator for identity

Simultaneous Image Transformation and Sparse Representation Recovery. Junzhou Huang 1 , Xiaolei Huang 2 , Dimitris Metaxas 1. 1 Division of Computer and Information Sciences, Rutgers University, NJ, USA 2 Department of Computer Science and Engineering, Lehigh University, PA, USA.

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Randomface : test image; : sparse indicator for identity

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  1. Simultaneous Image Transformation and Sparse Representation Recovery Junzhou Huang1, XiaoleiHuang2,Dimitris Metaxas1 1 Division of Computer and Information Sciences, Rutgers University, NJ, USA 2 Department of Computer Science and Engineering, Lehigh University, PA, USA Experiments on Face Data • Randomface • : test image; : sparse indicator for identity • Face recognition only and can handle the misaligned test image • Proposed TSR based approach • : test image; : sparse indicator for identity; : alignment parameter • Simultaneous face alignment and recognition as we can recover both and • Traditional video registration approach • Brightness constancy assumption • Cannot handle dynamic texture registration • Previous Dynamic texture approach • Registration and dynamic texture representation are separated • Cannot optimize the solution in one framework and thus the solutions are sub-optimal • not online • TSR based online registration • sparse representation constancy assumption • Given a new frame, its aligned version should be sparsely represented by the preceding frames • : the incoming new image frame; : sparse indicator based on preceding frames; : the registration parameter; : the measurement matrix based on preceding image frames TSR Based Face Alignment&Recognition • : linear measurements • : sparse signals • : measurement matrix • Sparse representation theory • Effectively reconstruct sparse signal x with measurements as few as possible • Geometry transformation problem? • : linear measurements • : sparse signals • : measurement matrix • : transformed version of y with parameter • Our solutions • Different measurement matrix, for example • Iteratively random manifold projection • Extended Yale B database • Moving flower bed sequence • 2.09% FEF; 5 seconds in MATLAB Sparse Representation Identification TSR Based Dynamic Texture Registration Transform-invariant Sparse Representation Figure. (a) Training images; (b) Test images; (c) Randomfaces[21]; (d) Proposed Verfication Experiments on Dynamic Scene Table. FEF of horizontal cumulative motion (Escalator Sequence) Figure. Cumulative motion; Left: horizontal; Right: Vertical

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