Facial Expression Recognition using Improved Adaptive Local Ternary Pattern


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Yadav , M and Saini, R and Sauravl, S and Singh, S (2018) Facial Expression Recognition using Improved Adaptive Local Ternary Pattern. In: 3rd International Conference on Computer Vision & Image Processing, September 29-October 01, 2018, IIIT , Jabalpur. (Submitted)

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Abstract. Recently, there has been a huge demand for assistive technology for industrial, commercial, automobile and societal applications. In such applications, there is a huge requirement of an efficient and accurate system for automatic facial expression recognition (FER). Therefore, FER has gained enormous interest in computer vision researchers. Although there has been a plethora of work available in the literature, an automatic FER system has not yet reached the desired level of robustness and performance. In most of these works, there has been the dominance of appearance-based methods such as local binary pattern (LBP), local directional pattern (LDP), local ternary pattern (LTP), gradient local ternary pattern (GLTP) and improved local ternary pattern (IGLTP) have been shown to be very efficient and accurate. In this paper, we have proposed a new descriptor called Improved Adaptive Local Ternary Pattern (IALTP) for automatic FER. This new descriptor is an improved version of ALTP which has been proved to be effective in face recognition. We have investigated ALTP in more detail and have proposed some improvements like the use of uniform patterns and dimensionality reduction via principal component analysis (PCA) are proposed. The reduced features are then classified using a kernel extreme learning machine (K-ELM) classifier. In order to validate the performance of the proposed method, experiments have been conducted on three different FER datasets. The performance has been observed using well I -known evaluation measures such as accuracy, precision, recall, and F I -Score. We have compared our proposed approach with some of the state-of-the-art works in literature and found it to be more accurate and efficient.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Keywords: Facial Expression Recognition (FER), Adaptive Local Ternary Pat- tern (ALTP), Improved Adaptive Local Ternary Pattern (I ALTP), Principal Component Analysis (PCA), and Kernel Extreme Learning Machine (K-ELM).
Subjects: Electronic Systems > Digital Systems
Divisions: Electronic Systems
Depositing User: Mr. Rabin Chatterjee
Date Deposited: 27 Jul 2021 09:50
Last Modified: 27 Jul 2021 09:50
URI: http://ceeri.csircentral.net/id/eprint/383

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