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

Publications associées (352)

A Constrained Latent Variable Model

Pascal Fua, Mathieu Salzmann, Raquel Urtasun, Aydin Varol

Latent variable models provide valuable compact representations for learning and inference in many computer vision tasks. However, most existing models cannot directly encode prior knowledge about the specific problem at hand. In this paper, we introduce a ...

Ieee2012

Finding Objects of Interest in Images using Saliency and Superpixels

Radhakrishna Achanta

The ability to automatically find objects of interest in images is useful in the areas of compression, indexing and retrieval, re-targeting, and so on. There are two classes of such algorithms – those that find any object of interest with no prior knowledg ...

EPFL2011

Are Sparse Representations Really Relevant for Image Classification?

Vincent Lepetit, Roberto Rigamonti, Matthew Brown

Recent years have seen an increasing interest in sparse representations for image classiﬁcation and object recognition, probably motivated by evidence from the analysis of the primate visual cortex. It is still unclear, however, whether or not sparsity hel ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Dynamic Quantification of Activity Recognition Capabilities in Opportunistic Systems

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha

Opportunistic activity and context recognition systems draw from the characteristic to use sensing devices according to a recognition goal at runtime that just happen to be available instead of pre-defining them at the design time of the system. Whenever a ...

2011

On the Convergence of EM-Like Algorithms for Image Segmentation using Markov Random Fields

Meritxell Bach Cuadra, Delphine Ribes Lemay, Gunnar Krüger, Alexis Roche

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad-hoc and ma ...

2011

Low complexity RST invariant image recognition using Fourier Mellin transform

Pierre-André Farine, Sara Grassi Pauletti, Pradyumna Ayyalasomayajula

In this paper we propose a low complexity method for Rotation, Scale and Translation (RST) invariant content-based image retrieval, suitable for a handheld image recognition device. The RST compensation method is based on Fourier-Mellin Transform (FMT) whi ...

EURASIP2011

Palm Vein Recognition with Local Binary Patterns and Local Derivative Patterns

Leila Mirmohamadsadeghi, Andrzej Drygajlo

Palm vein feature extraction from near infrared images is a challenging problem in hand pattern recognition. In this paper, a promising new approach based on local texture patterns is proposed. First, operators and histograms of multi-scale Local Binary Pa ...

2011

Parts-Based Face Verification using Local Frequency Bands

Sébastien Marcel

In this paper we extend the Parts-Based approach of face verification by performing a frequency-based decomposition. The Parts-Based approach divides the face into a set of blocks which are then considered to be separate observations, this is a spatial dec ...

Idiap2011

HEAT: Iterative Relevance Feedback with One Million Images

François Fleuret, Nicolae Suditu

It has been shown repeatedly that iterative relevance feedback is a very efficient solution for content-based image retrieval. However, no existing system scales gracefully to hundreds of thousands or millions of images. We present a new approach dubbed Hi ...

2011

HEAT: Iterative Relevance Feedback with One Million Images

François Fleuret, Nicolae Suditu

Idiap2011

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