PharmaPack: Mobile fine-grained recognition of pharma packages

We consider the problem of fine-grained physical object recognition and introduce a dataset PharmaPack containing 1000 unique pharma packages enrolled in a controlled environment using consumer mobile phones as well as several recognition sets representing various scenarios. For performance evaluati...

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Bibliographic Details
Published in2017 25th European Signal Processing Conference (EUSIPCO) pp. 1917 - 1921
Main Authors Taran, O., Rezaeifar, S., Dabrowski, O., Schlechten, J., Holotyak, T., Voloshynovskiy, S.
Format Conference Proceeding
LanguageEnglish
Published EURASIP 01.08.2017
Subjects
Europe
Feature extraction
Image recognition
Mobile communication
Mobile handsets
Signal processing
Visualization
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Summary:We consider the problem of fine-grained physical object recognition and introduce a dataset PharmaPack containing 1000 unique pharma packages enrolled in a controlled environment using consumer mobile phones as well as several recognition sets representing various scenarios. For performance evaluation, we extract two types of recently proposed local feature descriptors and aggregate them using popular tools. All enrolled raw and pre-processed images, extracted and aggregated descriptors are made public to promote reproducible research. To evaluate the baseline performance, we compare the methods based on aggregation of local descriptors with methods based on geometrical matching.
ISSN:2076-1465
DOI:10.23919/EUSIPCO.2017.8081543