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A novel feature extraction technique for expression recognition is proposed in this article. The proposed method exploits the properties of eigenvector decomposition in extracting the neutral and expression component of an expression containing test image. The methodology synthesizes a virtual neutral image from the given expression image of a person and(More)
The paper presents a simple but efficient novel H-eigenface (Hybrid-eigenface) method for pose invariant face recognition ranging from frontal to profile view. H-eigenfaces are entirely new basis for face image representation under different poses and are used for virtual frontal view synthesis. The proposed method is based on the fact that face samples of(More)
Ensuring a high level of service reliability is of paramount importance in an all-electric ship. In the literature, shipboard power systems (SPS) have been designed for improved survivability and quality of service (QOS) requirements. This paper presents a two-level topology design approach and develops system-level architectures for SPS that ensure(More)
This dissertation takes inspiration from the abilities of our brain to extract information and learn from multiple sources of data and try to mimic this ability for some practical problems. It explores the hypothesis that the human brain can extract and store information from raw data in a form, termed a common representation, suitable for cross-modal(More)