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Proceedings Paper

Products recognition on shop-racks from local scale-invariant features
Author(s): Jacek Zawistowski; Grzegorz Kurzejamski; Piotr Garbat; Jacek Naruniec
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Paper Abstract

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.

Paper Details

Date Published: 29 April 2016
PDF: 7 pages
Proc. SPIE 9896, Optics, Photonics and Digital Technologies for Imaging Applications IV, 989613 (29 April 2016); doi: 10.1117/12.2225610
Show Author Affiliations
Jacek Zawistowski, Warsaw Univ. of Technology (Poland)
Lingaro Sp. z o.o. (Poland)
Grzegorz Kurzejamski, Lingaro Sp. z o.o. (Poland)
Piotr Garbat, Warsaw Univ. of Technology (Poland)
Jacek Naruniec, Warsaw Univ. of Technology (Poland)

Published in SPIE Proceedings Vol. 9896:
Optics, Photonics and Digital Technologies for Imaging Applications IV
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal; Frédéric Truchetet; Pasi Saarikko, Editor(s)

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