Matrix Factorization-based clustering of image features for bandwidth-constrained information retrieval

Keyphrases

• Accurate Matching 50%
• Acquisition Process 50%
• Analysis Matrix 100%
• Bandwidth-constrained 100%
• Clustering Approach 50%
• Computational Complexity 50%
• Factor Loadings 50%
• Image Acquisition 50%
• Image Features 100%
• Image Matching 100%
• Information Content 50%
• Information Retrieval 100%
• Invariant Image Features 50%
• Matrix Factorization 100%
• Mobile Devices 50%
• Model Order 100%
• Non-negative Matrix Factorization 100%
• Number of Clusters 50%
• Number of Features 50%
• Principal Coordinate Analysis (PCoA) 100%
• Remote Server 50%
• Retrieval Accuracy 50%
• Scale Invariant 50%
• Small Clusters 50%
• SQL Server 50%
• Transmission Overhead 50%
• Trial-and-error 50%
• Urban Image 50%

Computer Science

• Acquisition Process 33%
• Captured Image 33%
• clustering approach 33%
• Component Analysis 66%
• Computational Complexity 33%
• Database Server 33%
• Image Acquisition 33%
• image feature 100%
• Image Matching 66%
• Information Content 33%
• Information Retrieval 100%
• Matrix Factorization 100%
• Mobile Device 33%
• nonnegative matrix factorization 33%
• Principal Components 66%
• Related Difference 33%
• retrieval accuracy 33%
• Retrieve Information 33%
• Transmission Overhead 33%