PT Journal
AU Lu Yu
   Lichao Zhang
   Joost Van de Weijer
   Fahad Shahbaz Khan
   Yongmei Cheng
   C. Alejandro Parraga
TI Beyond Eleven Color Names for Image Understanding
SO Machine Vision and Applications
JI MVAP
PY 2018
BP 361
EP 373
VL 29
IS 2
DI 10.1007/s00138-017-0902-y
DE Color name; Discriminative descriptors; Image classification; Re-identification; Tracking
AB 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.
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