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Finding Objects of Interest in Images using Saliency and Superpixels

Publications associées (102)

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Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

This paper presents 3-D brain tissue classification schemes using three recent promising energy minimization methods for Markov random fields: graph cuts, loopy belief propagation and tree-reweighted message passing. The classification is performed using t ...

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

Robust, High-Speed Interest Point Matching for Real-Time Applications

Michael Calonder

A typical Computer Vision system needs to process vast amounts of data as captured by one or more cameras, constantly testing the capabilities of today's hardware. Yet such systems face an ever-growing computational load caused by the more and more demandi ...

EPFL2010

Learning Pose Invariant and Covariant Classifiers from Image Sequences

Mustafa Özuysal

Object tracking and detection over a wide range of viewpoints is a long-standing problem in Computer Vision. Despite significant advance in wide-baseline sparse interest point matching and development of robust dense feature models, it remains a largely op ...

EPFL2010

Fast Bounding Box Estimation based Face Detection

Sébastien Marcel, Venkatesh Bala Subburaman

The sliding window approach is the most widely used technique to detect an object from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as cascade), the scan ...

2010

Material-Based Object Segmentation Using Near-Infrared Information

Sabine Süsstrunk, Neda Salamati

We present a framework to incorporate near-infrared (NIR) information into algorithms to better segment objects by isolating material boundaries from color and shadow edges. Most segmentation algorithms assign individual regions to parts of the object that ...

2010

Saliency Detection using Maximum Symmetric Surround

Sabine Süsstrunk, Radhakrishna Achanta

Detection of visually salient image regions is useful for applications like object segmentation, adaptive compression, and object recognition. Recently, full-resolution salient maps that retain well-defined boundaries have attracted attention. In these map ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Variational methods for texture segmentation

Nawal Houhou

In the last decades, image production has grown significantly. From digital photographs to the medical scans, including satellite images and video films, more and more data need to be processed. Consequently the number of applications based on digital imag ...

EPFL2009

Fast Texture Segmentation Based on Semi-local Region Descriptor and Active Contour

Jean-Philippe Thiran, Xavier Bresson, Nawal Houhou

In this paper, we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model. We address the problem of textures where neither the gray-l ...

2009

Fast Ray Features for Learning Irregular Shapes

Vincent Lepetit, Kevin Smith

We introduce a new class of image features, the Ray feature set, that consider image characteristics at distant contour points, capturing information which is difficult to represent with standard feature sets. This property allows Ray features to efficient ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Semi-Supervised Segmentation based on Non-local Continuous Min-Cut

Jean-Philippe Thiran, Xavier Bresson, Nawal Houhou

We propose a semi-supervised image segmentation method that relies on a non-local continuous version of the min-cut algorithm and labels or seeds provided by a user. The segmentation process is performed via energy minimization. The proposed energy is comp ...

Springer2009