Products recognition on shop-racks from local scale-invariant features

Jacek Zawistowski , Grzegorz Kurzejamski , Piotr Garbat , Jacek Naruniec


This paper presents a system designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. System uses well known binary keypoint detection algorithms for finding characteristic points in the image. One of the main idea is object recognition based on Implicit Shape Model method. Authors of the article proposed many improvements of the algorithm. Originally fiducial points are matched with a very simple function. This leads to the limitations in the number of objects parts being success- fully separated, while various methods of classification may be validated in order to achieve higher performance. Such an extension implies research on training procedure able to deal with many objects categories. Proposed solution opens a new possibilities for many algorithms demanding fast and robust multi-object recognition.
Author Jacek Zawistowski
Jacek Zawistowski,,
, Grzegorz Kurzejamski
Grzegorz Kurzejamski,,
, Piotr Garbat IMiO
Piotr Garbat,,
- The Institute of Microelectronics and Optoelectronics
, Jacek Naruniec IRTM
Jacek Naruniec,,
- The Institute of Radioelectronics and Multimedia Technology
Publication size in sheets0.5
Book Schelkens Peter, Ebrahimi Touradj, Cristóbal Gabriel, Truchetet Frédéric, Saarikko Pasi (eds.): Proceedings of SPIE Photonics Europe 2016: Optics, Photonics and Digital Technologies for Imaging Applications IV, vol. 9896, 2016, SPIE, ISBN 9781510601413, 500 p.
Languageen angielski
989613-3.pdf 704.67 KB
Score (nominal)15
ScoreMinisterial score = 15.0, 27-03-2017, BookChapterMatConf
Ministerial score (2013-2016) = 15.0, 27-03-2017, BookChapterMatConf
Citation count*0 (2018-07-16)
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