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NOVÁK, P. BURGET, R. KARÁSEK, J. DUTTA, M.
Originální název
Single template object detector based on histogram of oriented gradients
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Most of the current image object detection algorithms use very large data sets for their training and these methods are also optimized for those big data sets. Unfortunately, in many cases it is very costly or even impossible to collect large data sets for training (e.g. in medicine, astronomy, and other fields). In this paper a new approach based on Dalal's Histogram of Oriented Gradients (HOG) [3] is introduced. It is devoted for training from a single training template and is optimized to achieve reasonable accuracy with this limited training set. The accuracy is validated on 100 images, where half of them contains positive and the other half negative images. The accuracy achieved is 98%.
Klíčová slova
HOG, image object detection
Autoři
NOVÁK, P.; BURGET, R.; KARÁSEK, J.; DUTTA, M.
Rok RIV
2015
Vydáno
1. 7. 2015
Místo
Prague, Czech Republic
ISBN
978-1-4799-8498-5
Kniha
International Conference on Telecommunications and Signal Processing (TSP)
Edice
38
Strany od
508
Strany do
512
Strany počet
5
BibTex
@inproceedings{BUT117997, author="Pavel {Novák} and Radim {Burget} and Jan {Karásek} and Malay Kishore {Dutta}", title="Single template object detector based on histogram of oriented gradients", booktitle="International Conference on Telecommunications and Signal Processing (TSP)", year="2015", series="38", pages="508--512", address="Prague, Czech Republic", doi="10.1109/TSP.2015.7296367", isbn="978-1-4799-8498-5" }