Learning Color Names from Real-World Images
- 1 June 2007
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Within a computer vision context color naming is the action of assigning linguistic color labels to image pixels. In general, research on color naming applies the following paradigm: a collection of color chips is labelled with color names within a well-defined experimental setup by multiple test subjects. The collected data set is subsequently used to label RGB values in real-world images with a color name. Apart from the fact that this collection process is time consuming, it is unclear to what extent color naming within a controlled setup is representative for color naming in real-world images. Therefore we propose to learn color names from real-world images. Furthermore, we avoid test subjects by using Google Image to collect a data set. Due to limitations of Google Image this data set contains a substantial quantity of wrongly labelled data. The color names are learned using a PLSA model adapted to this task. Experimental results show that color names learned from real-world images significantly outperform color names learned from labelled color chips on retrieval and classification.Keywords
This publication has 14 references indexed in Scilit:
- Latent Mixture Vocabularies for Object CategorizationPublished by British Machine Vision Association and Society for Pattern Recognition ,2006
- Image region entropyPublished by Association for Computing Machinery (ACM) ,2005
- Modeling scenes with local descriptors and latent aspectsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Discovering objects and their location in imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Learning object categories from Google's image searchPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- 10.1162/153244303322533214Applied Physics Letters, 2000
- Probabilistic latent semantic indexingPublished by Association for Computing Machinery (ACM) ,1999
- Is machine colour constancy good enough?Published by Springer Nature ,1998
- Color constant color indexingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1995
- A novel algorithm for color constancyInternational Journal of Computer Vision, 1990