Learning-Based Local Visual Representation and Indexing

Chapter 3

Unsupervised Dictionary Optimization

Abstract

The core part of the learning-based local representation lies in the visual dictionary and its indexing structure, e.g., how to optimize the local feature-space quantization scheme. In Chapter 2, the design of the optimal interest-point detector was covered, while in this chapter, we introduce and discuss the way to optimize the dictionary construction-based on hierarchical metric learning unsupervised. We will show that the traditional Euclidean distance-based metric is unsuitable for k-means clustering, which would push clusterings located at dense regions and hence result in a biased distance metric. To deal with this issue, this chapter introduces density-based metric learning (DML) ...