Bag-of-Features Image Indexing and Classification in Microsoft SQL Server Relational Database
arXiv:1506.07950v112 citations
Originality Synthesis-oriented
AI Analysis
This work addresses image management challenges for database users, but it appears incremental as it combines existing methods in a new system.
The paper tackles the problem of visual object classification and retrieval by introducing a relational database architecture that integrates bag-of-features representation with SVM classification in Microsoft SQL Server, resulting in a framework for efficient image indexing and classification.
This paper presents a novel relational database architecture aimed to visual objects classification and retrieval. The framework is based on the bag-of-features image representation model combined with the Support Vector Machine classification and is integrated in a Microsoft SQL Server database.