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Saliency-based Representations and Multi-component Classifiers for Visual Scene Recognition

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Classification of dog barks: a machine learning approach

Frédéric Kaplan

In this study we analyzed the possible context-specific and individual-specific features of dog barks using a new machine-learning algorithm. A pool containing more than 6,000 barks, which were recorded in six different communicative situations was used as ...

2008

Finger-spelling Recognition within a Collaborative Segmentation/Behavior Inference Framework

Jean-Philippe Thiran, Laura Ioana Gui

We introduce a new approach for finger-spelling recognition from video sequences, relying on the collaboration between the feature extraction and behavior inference processes. The inference process dynamically guides the segmentation- based feature extract ...

2008

Segmenting memory colours

Sabine Süsstrunk, Francisco Estrada

Memory colours refer to the colour of specific image classes that have the essential attribute of being perceived in a consistent manner by human observers. In colour correction or rendering tasks, this consistency implies that they have to be faithfully r ...

2008

Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder

Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods hav ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2008

Discriminative cue integration for medical image annotation

Barbara Caputo, Tatiana Tommasi

Automatic annotation of medical images is an increasingly important tool for physicians in their daily activity. Hospitals nowadays produce an increasing amount of data. Manual annotation is very costly and prone to human mistakes. This paper proposes a mu ...

2008

Ensembles of SVMs using an Information Theoretic Criterion

Jean-Philippe Thiran, Julien Meynet

Training Support Vector Machine can become very challenging in large scale problems. Training several lower complexity SVMs on local subsets of the training set can significantly reduce the training complexity and also improve the classification performanc ...

2008

CLEF2008 Image Annotation Task: an SVM Confidence-Based Approach

Barbara Caputo, Tatiana Tommasi

This paper presents the algorithms and results of our participation to the medi- cal image annotation task of ImageCLEFmed 2008. Our previous experience in the same task in 2007 suggests that combining multiple cues with diﬀerent SVM-based approaches is ve ...

Idiap2008

A multimodal pattern recognition framework for speaker detection

Patricia Besson

Speaker detection is an important component of a speech-based user interface. Audiovisual speaker detection, speech and speaker recognition or speech synthesis for example find multiple applications in human-computer interaction, multimedia content indexin ...

EPFL2007

Confidence-based Cue Integration for Visual Place Recognition

Barbara Caputo

A distinctive feature of intelligent systems is their capability to analyze their level of expertise for a give task; in other words, they know what they know. As a way towards this ambitious goal, this paper presents an algorithm for recognition able to m ...

IDIAP2007

Information theoretic combination of classifiers with application to face detection

Julien Meynet

Combining several classifiers has become a very active subdiscipline in the field of pattern recognition. For years, pattern recognition community has focused on seeking optimal learning algorithms able to produce very accurate classifiers. However, empiri ...

EPFL2007