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Adaptive Relevance Feedback for Large-scale Image Retrieval

Publications associées (65)

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Co-occurrence Models for Image Annotation and Retrieval

Nikhil Garg

We present two models for content-based automatic image annotation and retrieval in web image repositories, based on the co-occurrence of tags and visual features in the images. In particular, we show how additional measures can be taken to address the noi ...

Idiap2009

Image Summaries using Database Saliency

Pascal Fua, Sabine Süsstrunk, Radhakrishna Achanta, Appu Shaji

It is useful to have a small set of representative images from a database of thousands of images to summarize its content. There are two key aspects of such image summaries: how to generate them and how to present them. We address both issues. We extend th ...

2009

Retrieving Ancient Maya Glyphs with Shape Context

Daniel Gatica-Perez, Jean-Marc Odobez, Edgar Roman Rangel

We introduce an interdisciplinary project for archaeological and computer vision research teams on the analysis of the ancient Maya writing system. Our first task is the automatic retrieval of Maya syllabic glyphs using the Shape Context descriptor. We inv ...

IEEE2009

A collaborative approach to image segmentation and behavior recognition from image sequences

Laura Ioana Gui

Visual behavior recognition is currently a highly active research area. This is due both to the scientific challenge posed by the complexity of the task, and to the growing interest in its applications, such as automated visual surveillance, human-computer ...

EPFL2008

The Flux: Creating a Large Annotated Image Database

Sabine Süsstrunk, Patrick Vandewalle, Daniel Tamburrino, Patrick Merryl Marlon Schönmann

From image retrieval to image classification, all research shares one common requirement: a good image database to test or train the algorithms. In order to create a large database of images, we set up a project that allowed gathering a collection of more ...

2008

Machine learning for information retrieval

David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...

EPFL2008

Machine Learning for Information Retrieval

David Grangier

École Polytechnique Fédérale de Lausanne2008

Machine Learning for Information Retrieval

David Grangier

IDIAP2008

Learning the structure of image collections with latent aspect models

Florent Monay Michaud

The approach to indexing an image collection depends on the type of data to organize. Satellite images are likely to be searched with latitude and longitude coordinates, medical images are often searched with an image example that serves as a visual query, ...

École Polytechnique Fédérale de Lausanne2007

Learning the structure of image collections with latent aspect models

Florent Monay Michaud

IDIAP2007