Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Encoding Optimization Using Nearest Neighbor Descriptor
verfasst von : Muhammad Rauf, Yongzhen Huang, Liang Wang
Erschienen in: Pattern Recognition
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The Bag-of-words framework is probably one of the best models used in image classification. In this model, coding plays a very important role in the classification process. There are many coding methods that have been proposed to encode images in different ways. The relationship between different codewords is studied, but the relationship among descriptors is not fully discovered. In this work, we aim to draw a relationship between descriptors, and propose a new method that can be used with other coding methods to improve the performance. The basic idea behind this is encoding the descriptor not only with its nearest codewords but also with the codewords of its nearest neighboring descriptors. Experiments on several benchmark datasets show that even using this simple relationship between the descriptors helps to improve coding methods.