Details

Autor(en) / Beteiligte

• Kumaki, K.
• Nankaku, Y.
• Tokuda, K.

Titel

Face recognition based on extended separable lattice 2-D HMMS

Ist Teil von

• 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012, p.2209-2212

Ort / Verlag

IEEE

Erscheinungsjahr

2012

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• This paper proposes an extension of separable lattice 2-D hidden Markov models (SL-HMMs) for dealing with image rotation and local deformation. It is important to reduce the effect of geometrical variations in image recognition, e.g., location, size, and rotation. SLHMMs are one of the most efficient structures to accomplish invariance to size and location variations. However, since SL-HMMs only have one state sequence in each direction, they cannot deal with rotation or local deformation. The proposed models have state sequences corresponding to all rows and columns of an input image, and the complicated state alignments can represent rotation and local deformation. The effectiveness of the proposed models was demonstrated in face recognition experiments.