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Hierarchical Classification for Live Fish Recognition

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Original languageEnglish
Title of host publicationBritish Machine Vision Conference 2012 Student Workshop
EditorsTeofilo de Campos
Publication statusPublished - 7 Sep 2012

Abstract

Live fish recognition in the open sea is a challenging multi-class classification task. We propose a hierarchical classification approach to recognize live fish from underwater videos. However, the hierarchical method accumulates misclassified samples into deeper layers and these accumulated errors reduce the average accuracy. We propose a set of heuristics to help construct more accurate hierarchical trees and, therefore, control the error accumulation. We create an automatically generated tree based on these heuristics and compare it to a baseline tree on a live fish image dataset. The proposed hierarchical classification method achieves about 4% better accuracy compared to state-of-the-art techniques.

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