Concept

Feature (computer vision)

Related publications (683)

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FREAK: Fast Retina Keypoint

Pierre Vandergheynst, Alexandre Massoud Alahi, Raphaël Ortiz

A large number of vision applications rely on matching keypoints across images. The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: Scale Invariant Feature Transform (SIFT), Speed-up Robust Feature (SU ...

Ieee2012

A New In-Camera Imaging Model for Color Computer Vision and its Application

Sabine Süsstrunk, Seungryong Kim, Matthew Brown

We present a study of the in-camera image processing through an extensive analysis of more than 10,000 images from over 30 cameras. The goal of this work is to investigate if image values can be transformed to physically meaningful values, and if so, when ...

Institute of Electrical and Electronics Engineers2012

Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition

David Imseng, Ramya Rasipuram

One of the main challenge in non-native speech recognition is how to handle acoustic variability present in multiaccented non-native speech with limited amount of training data. In this paper, we investigate an approach that addresses this challenge by usi ...

Idiap2012

Assessing Sparse Coding Methods for Contextual Shape Indexing of Maya Hieroglyphs

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

Bag-of-visual-words or bag-of-visterms (bov) is a common technique used to index Multimedia information with the purposes of retrieval and classification. In this work we address the problem of constructing efficient bov representations of complex shapes a ...

2012

Removing Shadows from Images Using Color and Near-infrared

Sabine Süsstrunk, Neda Salamati, Arthur Germain

Shadows often introduce errors in the performance of computer vision algorithms, such as object detection and tracking. This paper proposes a method to remove shadows from real images based on a probability shadow map. The probability shadow map identifies ...

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

Fast human detection from joint appearance and foreground feature subset covariances

Jean-Marc Odobez

We present a fast method to detect humans from stationary surveillance videos. It is based on a cascade of LogitBoost classifiers which use covariance matrices as object descriptors. We have made several contributions. First, our method learns the correlat ...

2011

Object Duplicate Detection

Péter Vajda

With the technological evolution of digital acquisition and storage technologies, millions of images and video sequences are captured every day and shared in online services. One way of exploring this huge volume of images and videos is through searching a ...

EPFL2011

Multispectral Interest Points for RGB-NIR Image Registration

Sabine Süsstrunk, Matthew Brown, Damien Firmenich

This paper explores the use of joint colour and near-infrared (NIR) information for feature based matching and image registration. In particular, we investigate multispectral generalisations of two popular interest point detectors (Harris and difference of ...

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

Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models

Matthias Seeger

Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or super-resolution, can be addressed by maximizing the posterior distribution of a sparse linear model (SLM). We show how higher- ...

2011

Computing correspondences in geometric data sets

Mark Pauly, Hao Li

Shape registration and, more generally speaking, computing correspondence across shapes are fundamental problems in computer graphics and vision. Problems from this area show up in many diff erent variants such as scan registration, deformable shape matchi ...

2011