| ||Evaluating Color Descriptors for Object and Scene Recognition|
In IEEE Transactions on Pattern Analysis and Machine Intelligence 2010.
[bibtex] [pdf] [url]
Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition.
Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a dataset with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain.
From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results reveal further that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the dataset and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8% on the PASCAL VOC 2007 and by 7% on the Mediamill Challenge.
Color descriptor software is available for download
Software to compute the color descriptors from this paper is available from http://www.colordescriptors.com
Digital Object Identifier: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2009.154
author = "van de Sande, K. E. A. and Gevers, T. and Snoek, C. G. M.",
title = "Evaluating Color Descriptors for Object and Scene Recognition",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
number = "9",
volume = "32",
pages = "1582--1596",
year = "2010",
url = "https://ivi.fnwi.uva.nl/isis/publications/2010/vandeSandeTPAMI2010",
pdf = "https://ivi.fnwi.uva.nl/isis/publications/2010/vandeSandeTPAMI2010/vandeSandeTPAMI2010.pdf",
has_image = 1