Compact codebook creation and local feature coding in bag-of-features model for image classification
Bag-of-features model is an effective framework for generating image representation and has been established as the state-of-the-art for image categorization. In general, it consists of four key modules: local feature extraction, codebook generation, feature coding and feature pooling. In practice, the realization of these four modules is very flexible. While leaving a large room for performance improvement, this flexibility also raises many open issues in the research of bag-of-features model....[Show more]
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