Evaluation of Second-order Visual Features for Land-Use Classification

Romain Negrel (1) , David Picard (1) , Philippe-Henri Gosselin (2, 1)

1 MIDI - Multimedia Indexation and Data Integration
2 TEXMEX - Multimedia content-based indexing

This paper investigates the use of recent visual features based on second-order statistics, as well as new pro- cessing techniques to improve the quality of features. More specifically, we present and evaluate Fisher Vectors (FV), Vec- tors of Locally Aggregated Descriptors (VLAD), and Vectors of Locally Aggregated Tensors (VLAT). These techniques are combined with several normalization techniques, such as power law normalization and orthogonalisation/whitening of descriptor spaces. Results on the UC Merced land use dataset shows the relevance of these new methods for land-use classification, as well as a significant improvement over Bag-of-Words.

Domains: Computer Vision and Pattern Recognition [cs.CV]

Romain Negrel, David Picard, Philippe-Henri Gosselin. Evaluation of Second-order Visual Features for Land-Use Classification. 12th International Workshop on Content-Based Multimedia Indexing, Jun 2014, France. 5 p. ⟨hal-01022971⟩