Beyond Eleven Color Names for Image Understanding

Color description is one of the fundamental problems of image understanding. One of the popular ways to represent colors is by means of color names. Most existing work on color names focuses on only the eleven basic color terms of the English language. This could be limiting the discriminative power...

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Bibliographic Details
Published in:Machine vision and applications 2018-02, Vol.29 (2), p.361-373
Main Authors: Yu, Lu, Zhang, Lichao, van de Weijer, Joost, Khan, Fahad Shahbaz, Cheng, Yongmei, Parraga, C. Alejandro
Format: Article
Language:English
Subjects:
Color
Communications Engineering
Computer Science
English language
Image classification
Image Processing and Computer Vision
Layouts
Names
Networks
Optical tracking
Original Paper
Pattern Recognition
Personal communication
Representations
Response time
Software utilities
Vision systems
Visual tasks
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Summary:Color description is one of the fundamental problems of image understanding. One of the popular ways to represent colors is by means of color names. Most existing work on color names focuses on only the eleven basic color terms of the English language. This could be limiting the discriminative power of these representations, and representations based on more color names are expected to perform better. However, there exists no clear strategy to choose additional color names. We collect a dataset of 28 additional color names. To ensure that the resulting color representation has high discriminative power we propose a method to order the additional color names according to their complementary nature with the basic color names. This allows us to compute color name representations with high discriminative power of arbitrary length. In the experiments we show that these new color name descriptors outperform the existing color name descriptor on the task of visual tracking, person re-identification and image classification.
ISSN:0932-8092
1432-1769
1432-1769
DOI:10.1007/s00138-017-0902-y