TY  - JOUR
AU  - Lu Yu
AU  - Lichao Zhang
AU  - Joost Van de Weijer
AU  - Fahad Shahbaz Khan
AU  - Yongmei Cheng
AU  - C. Alejandro Parraga
PY  - 2018//
TI  - Beyond Eleven Color Names for Image Understanding
T2  - MVAP
JO  - Machine Vision and Applications
SP  - 361
EP  - 373
VL  - 29
IS  - 2
KW  - Color name
KW  - Discriminative descriptors
KW  - Image classification
KW  - Re-identification
KW  - Tracking
N2  - 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.
L1  - http://refbase.cvc.uab.es/files/YYW2018.pdf
UR  - http://dx.doi.org/10.1007/s00138-017-0902-y
N1  - LAMP; NEUROBIT; 600.068; 600.109; 600.120
ID  - Lu Yu2018
ER  -