Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
A Discrete Direct Retrieval Model For Image And Video Retrieval, Shaolei Feng, R. Manmatha
A Discrete Direct Retrieval Model For Image And Video Retrieval, Shaolei Feng, R. Manmatha
R. Manmatha
This paper proposes a formal framework for image and video retrieval using discrete Markov random fields(MRF). The training dataset consists of images with keywords (regions are not labeled). The model may be built using quantized region or point features generated from the training images. Unlike many previous techniques, our MRF based model doesn't require an explicit annotation step for retrieval. The model directly ranks all test images according to the posterior probability of an image given a query. Image and video retrieval experiments are performed on two standard datasets (one Corel datasets and a TRECVID3 dataset) which consist of 4,500 …
Joint Visualtext Modeling For Automatic Retrieval Of Multimedia Documents, G. Iyengar, P. Duygulu, S. Feng, P. Ircing, S. P. Khudanpur, D. Klakow, M. R. Krause, R. Manmatha, H. J. Nock, D. Petkova, B. Pytlik, P. Virga
Joint Visualtext Modeling For Automatic Retrieval Of Multimedia Documents, G. Iyengar, P. Duygulu, S. Feng, P. Ircing, S. P. Khudanpur, D. Klakow, M. R. Krause, R. Manmatha, H. J. Nock, D. Petkova, B. Pytlik, P. Virga
R. Manmatha
In this paper we describe our approach for jointly modeling the text part and the visual part of multimedia documents for the purpose of information retrieval(IR). In the prevalent state-of-the-art systems, a late combination between two independent systems, one analyzing just the text part of such documents, and the other analyzing the visual part without leveraging any knowledge acquired in the text processing, is the norm. Such systems rarely exceed the performance of any single modality (i.e. text or video) in information retrieval tasks. Our experiments indicate that allowing a rich interaction between the modalities results in signi.- cant improvement …
A Search Engine For Historical Manuscript Images, Toni M. Rath, R. Manmatha, Victor Lavrenko
A Search Engine For Historical Manuscript Images, Toni M. Rath, R. Manmatha, Victor Lavrenko
R. Manmatha
Many museum and library archives are digitizing their large collections of handwritten historical manuscripts to enable public access to them. These collections are only available in image formats and require expensive manual annotation work for access to them. Current handwriting recognizers have word error rates in excess of 50% and therefore cannot be used for such material. We describe two statistical models for retrieval in large collections of handwritten manuscripts given a text query. Both use a set of transcribed page images to learn a joint probability distribution between features computed from word images and their transcriptions. The models can …