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Face recognition in JPEG compressed domain is one of the recent challenges in biometric systems, leading to a considerable reduction in computational overhead caused by decompression process, without any notable degradation in the recognition rates. In this paper, the potential of using a limited number of lowest frequency coefficients in JPEG compressed domain face recognition is investigated, to...
Facial expression recognition plays an important role in interactive entertainment. In this paper, LSFA (Local Sensitive Frontier Analysis) a novel feature extraction method is introduced for facial expression recognition. LSFA is designed as manifold based feature extraction method to obtain useful features from the facial expression pictures, since the facial expression scatter in high dimensional...
Over the last decade, automated analysis of human affective behavior has become an active research area in computer science, psychology, neuroscience, and related fields. This study investigates the application of Gabor filter based features in combination of Genetic Algorithm (GA) and Support Vector Machine (SVM) for dynamic analysis of six basic facial expressions from video sequences. Traditionally,...
People with Cerebral Palsy (CP) suffer from speech, physical and intellectual disabilities. Many augmentative and alternative communication tools (AAC) have been developed and recommended by speech pathologies to improve their communication ability. However, the existing recommended AAC tools seem to be less efficient as they focused on text-to-speech, speech-to-text or touch-screen. They required...
We propose in this paper a multilinear locality preserving canonical correlation analysis (MLPCCA) method for face recognition. Motivated by the fact that both spatial structure information within each face sample and local geometry information among multiple face samples are useful for facial image feature extraction, we utilize them simultaneously and derive an improved canonical correlation analysis...
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