Computational Salience Based Approach for Print Quality Assessment
The VisiQ is developing an unsupervised method to categorize an unknown set of images into seperate clusters.
The goal of the project is to develop a system that is able to categorize a set of unknown images. Images should be categorized based on objects that images consist of. The system must be unsupervised, hence it cannot have any prior information about the images, e.g. class labels, training images, etc.
- Randomized Caltech 101 image set published and added to the webpage. Please see the downloads section.
- Page updated. New links added to a image database and rival systems.
- Unsupervised VOC www-demo published. Try! Limited access.
- Website published.
|Lappeenranta University of Technology|
|Teemu Kinnunen||WWW||Doctoral student, Master of science|
|Lasse Lensu||WWW||Associate Professor||Heikki Kälviäinen||WWW||Professor|
|Helsinki University of Technology||Mari Laine-Hernandez||not available||Doctoral student, Master of science||Pirkko Oittinen||not available||Professor|
This project is part of the research in the Machine Vision and Pattern Recognition Research Group.
- Randomized Caltech 101 dataset: RandomizedCaltech101.tar.gz [113MB]
- Randomized Caltech 101 Mask files: RandomizedCaltech101Masks.tar.gz [5.9MB]
Demo is based on the system that was developed for Kinnunen's Master's thesis Unsupervised visual object categorization, (2008).WWW-DEMO (Limited access)
Links to other resources
Image search engines
- ImageCLEF Homepage
Databases and competitions
- Fei-Fei Li: Homepage
- David Lowe: Homepage
- Andrew Zisserman: Homepage
- Andrea Vedaldi: Homepage
- Tamara L. Berg: Homepage
- Charles Leek: Homepage (psychology)
- John E. Hummel: Homepage (psychology)
- Gert Kootstra: Homepage (Saliency detection, Active vision, SLAM, etc)
Image categorization systems
Interest points (detectors and descriptors)
- Discriminant Saliency Detection: Statistical Visual Computing Lab, UCSD
Do not hesitate to contact authors (e-mail, etc.) in order to retrieve copies or reprints of the following publications.