Fast color-based object recognition independent of position and orientation

Martijn Van De Giessen; Jürgen Schmidhuber

doi:10.1007/11550822_73

Fast color-based object recognition independent of position and orientation

Martijn Van De Giessen, Jürgen Schmidhuber

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

Small mobile robots typically have little on-board processing power for time-consuming vision algorithms. Here we show how they can quickly extract very dense yet highly useful information from color images. A single pass through all pixels of an image serves to segment it into color-dependent regions and to compactly represent it by a short list of the average hues, saturations and color intensities of its regions; all other information is discarded. Experiments with two image databases show that in 90% of all cases the remaining information is sufficient for a simple weighted voting algorithm to recognize objects shown in query images, independently of position and orientation and partial occlusions. © Springer-Verlag Berlin Heidelberg 2005.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	469-474
Number of pages	6
ISBN (Print)	3540287523
DOIs	https://doi.org/10.1007/11550822_73
State	Published - Jan 1 2005

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10.1007/11550822_73

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title = "Fast color-based object recognition independent of position and orientation",

abstract = "Small mobile robots typically have little on-board processing power for time-consuming vision algorithms. Here we show how they can quickly extract very dense yet highly useful information from color images. A single pass through all pixels of an image serves to segment it into color-dependent regions and to compactly represent it by a short list of the average hues, saturations and color intensities of its regions; all other information is discarded. Experiments with two image databases show that in 90% of all cases the remaining information is sufficient for a simple weighted voting algorithm to recognize objects shown in query images, independently of position and orientation and partial occlusions. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.",

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Fast color-based object recognition independent of position and orientation. / Van De Giessen, Martijn; Schmidhuber, Jürgen.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2005. p. 469-474.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Small mobile robots typically have little on-board processing power for time-consuming vision algorithms. Here we show how they can quickly extract very dense yet highly useful information from color images. A single pass through all pixels of an image serves to segment it into color-dependent regions and to compactly represent it by a short list of the average hues, saturations and color intensities of its regions; all other information is discarded. Experiments with two image databases show that in 90% of all cases the remaining information is sufficient for a simple weighted voting algorithm to recognize objects shown in query images, independently of position and orientation and partial occlusions. © Springer-Verlag Berlin Heidelberg 2005.

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Fast color-based object recognition independent of position and orientation

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