Improved labelling for Pedestrian Detection, INRIA data set
Автор: Matteo Taiana
Загружено: 2013-06-27
Просмотров: 6136
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Abstract:
Data sets are a fundamental tool for comparing detection algorithms, fostering advances in the state of the art. The INRIA person data set is very popular in the Pedestrian Detection community, both for training detectors and reporting results. Yet, the labelling of its test set has some limitations: some of the pedestrians are not labelled, there is no specific label for the ambiguous cases and the information on the visibility ratio of each person is missing. We present a new labelling that overcomes such limitations and show that it can be used to evaluate the performance of detection algorithms in a more truthful way.
Download the new labelling here:
http://users.isr.ist.utl.pt/~mtaiana/...
Download the paper here:
http://welcome.isr.ist.utl.pt/img/pdf...
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