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Research Paper | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014 | Rating: 6.2 / 10
Use of ?2/3-norm Sparse Representation for Facial Expression Recognition
Sandeep Rangari, Sandeep Gonnade
Abstract: In this particular paper, we recommend a brand new sparse rendering primarily based group via 2/3norm minimization with regard to facial Expression Recognition. All of us work with 2/3-norm minimization instead of 2/3-norm minimization with regard to sparser, a lot more identification fee and many correct options, lowest computing moment and optimization dilemma connected with 2/3-norm minimization. This 2/3-norm regularize is actually open to get a wide range of ensuring components such as neutral, eye-sight and sparsity components. All of us work with 2/3-norm minimization (2/3 SRC) as an alternative to 2/3-norm minimization (2/3 SRC). Additionally, the active-set primarily based iterative reweighted criteria are actually recommended to fix your 2/3-Norm minimization dilemma. This trial and error effects with JAFFE Database/sources state your productivity connected with 2/3-SRC.
Keywords: Sparse Representation, 1/2norm minimization, 2/3-norm minimization, Facial Expression Recognition
Edition: Volume 3 Issue 11, November 2014,
Pages: 388 - 391