(to be updated soon)
We are investigating innovative
techniques using integrated multimedia features for automatic image classification.
This is a collaborative project with the Natural Language Processing group
at Columbia. On the image side, we are developing a new approach, called
OF*IIF (Object Frequency * Inverse Image Frequency), to automatically
extract the discriminative objects and their distribution from single
images or classes of images. The OF*IIF feature vector has been proved
to be effective compared to other state-of-the-art image classifiers.
It achieves significant performance gain when combined with the popular
text-based approach, TF*IIF.
We are currently developing
tan integration framework using Bayesian Networks for combining text-based
and visual-based feature vectors for classifying images to different categories
such as indoor/outdoor, people, handshake, etc. The demo shows automatic
classification using combined text-visual features.
For problems or questions
regarding this web site contact The
Last updated: June 12, 2002.