Scale and Rotation Invariant Matching Using Linearly Augmented Trees PROJECT TITLE :Scale and Rotation Invariant Matching Using Linearly Augmented TreesABSTRACT:We propose a completely unique linearly augmented tree technique for economical scale and rotation invariant object matching. The proposed method enforces pairwise matching consistency outlined on trees, and high-order constraints on all the sites of a template. The pairwise constraints admit arbitrary metrics while the high-order constraints use L1 norms and thus can be linearized. Such a linearly augmented tree formulation introduces hyperedges and loops into the fundamental tree structure. However, different from a general loopy graph, its special structure permits us to relax and decompose the optimization into a sequence of tree matching issues that are efficiently solvable by dynamic programming. The proposed technique also works on continuous scale and rotation parameters; we tend to can match with a scale up to any large price with the identical efficiency. Our experiments on ground truth knowledge and a selection of real pictures and videos show that the proposed technique is efficient, accurate and reliable. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Stochastic Control for Linear Systems With Additive Cauchy Noises Injection Locked Wavelength De-Multiplexer for Optical Comb-Based Nyquist WDM System
