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NOVÁK, P. BURGET, R. KARÁSEK, J. DUTTA, M.
Original Title
Single template object detector based on histogram of oriented gradients
Type
conference paper
Language
English
Original Abstract
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%.
Keywords
HOG, image object detection
Authors
NOVÁK, P.; BURGET, R.; KARÁSEK, J.; DUTTA, M.
RIV year
2015
Released
1. 7. 2015
Location
Prague, Czech Republic
ISBN
978-1-4799-8498-5
Book
International Conference on Telecommunications and Signal Processing (TSP)
Edition
38
Pages from
508
Pages to
512
Pages count
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" }