IBM Research Australia at LifeCLEF2014: Plant Identification Task.

Abstract

In this paper, we present the system and learning strategies that were applied by the IBM Research team to the plant identication task of LifeCLEF 2014. Plant identication is one of the most popular ne-grained categorization tasks. To ensure high classication accuracy, we have utilised strong visual features together with fusion of robust machine learning techniques. Our proposed system involves automatic delineation of the region of interest (e.g. plant's leaf, ower, etc.) in the given image, followed by extracting multiple complementary low level features. The features have been then encoded into the sophisticated Fisher Vector representation which enables accurate classication with