International Journal of Electrical, Electronics and Data Communication (IJEEDC)
eISSN:2320-2084 , pISSN:2321-2950
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Jul. 2024
Submitted Papers : 80
Accepted Papers : 10
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Acc. Perc : 12%
Issue Published : 136
Paper Published : 1737
No. of Authors : 4816
  Journal Paper

Paper Title :
Lip Recognition Using Various Neural Classifiers

Author :Shoureya Kant, Rahul Kala, Ritu Tiwari, Anupam Shukla, Samridha Kumar

Article Citation :Shoureya Kant ,Rahul Kala ,Ritu Tiwari ,Anupam Shukla ,Samridha Kumar , (2016 ) " Lip Recognition Using Various Neural Classifiers " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 86-94, Volume-4,Issue-10

Abstract : In this paper we attempt at presenting a detailed comparative study of lip recognition based on Principle Component Analysis (PCA) which is used for feature extraction for various classifiers. The classifiers include different Artificial Neural Networks (ANN) like Back Propagation (BP), Layer-Recurrent Network (LRN), Radial Basis Network (RBN), Modular Neural Network (MNN) with input space partitioning and neural network ensembles. Here, we have chosen “TULIPS1 database” which is a small audiovisual database of 7 subjects for the incorporation of above methods. The paper presents a systematic approach where we start by trying to figure out the ideal number of PCA coefficients, network models, and network architectures for the considered problem. We later attempt to use these readings to make effective hybrid classifiers. Experimental results confirm that using the approach, we can get effective classifiers that are characterized by effective recognition rates. Index terms- Lip Features; Principal Component Analysis; Back Propagation; Layer-Recurrent Network; Radial Basis Network; Modular Neural Network; Ensembles; Fuzzy C- Means Clustering.

Type : Research paper

Published : Volume-4,Issue-10


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