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Enhanced locality sensitive discriminant analysis for image recognition

Enhanced locality sensitive discriminant analysis for image recognition

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© The Institution of Engineering and Technology
Published

An improved manifold learning method, called enhanced locality sensitive discriminant analysis (ELSDA), for image recognition is proposed. Motivated by the fact that statistically uncorrelated and parameter-free are two desirable and promising characteristics for feature extraction, a new difference-based optimisation objective function with uncorrelated constraint for appearance-based image recognition has been designed. Experimental results demonstrate the efficacy of the proposed method.

Inspec keywords: learning (artificial intelligence); feature extraction; optimisation; image recognition

Other keywords: manifold learning method; feature extraction; enhanced locality sensitive discriminant analysis; difference-based optimisation objective function; appearance-based image recognition

Subjects: Knowledge engineering techniques; Optimisation techniques; Image recognition; Computer vision and image processing techniques; Image recognition; Optimisation techniques

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