Publications related to OmniSIFT: Scale Invariant Features in Omnidirectional Images

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...

École Polytechnique Fédérale de Lausanne2007

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Pedro Manuel Da Silva Quelhas

The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...

EPFL2007

Optimal control of geodesics in Riemannian manifolds

Roland Rozsnyo

The aim of this dissertation is to solve numerically the following problem, denoted by P : given a Riemannian manifold and two points a and b belonging to that manifold, find a tangent vector T at a, such that expa(T) = b, assuming that T exists. This prob ...

EPFL2007

Scale-space analysis and active contours for omnidirectional images

Jean-Philippe Thiran, Pierre Vandergheynst, Xavier Bresson, Iva Bogdanova Vandergheynst

A new generation of optical devices that generate images covering a larger part of the field of view than conventional cameras, namely catadioptric cameras, is slowly emerging. These omnidirectional images will most probably deeply impact computer vision i ...

Institute of Electrical and Electronics Engineers2007

Orientation histogram-based matching for Region Tracking

Touradj Ebrahimi

A region tracking technique with particular emphasis on rotation robustness is presented. It is based on region matching divided in two consecutive steps, gradient orientation histogram matching and template matching through Normalised Cross Correlation (N ...

2007

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Daniel Gatica-Perez, Jean-Marc Odobez, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas

We present a novel approach for contextual segmentation of complex visual scenes, based on the use of bags of local invariant features (visterms) and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that specific le ...

2006

Laplacian Operator, Diffusion Flow and Active Contour on non-Euclidean Images

Jean-Philippe Thiran, Pierre Vandergheynst, Xavier Bresson, Iva Bogdanova Vandergheynst

We propose here some basic approaches to direct processing of the

360^o

-images as we take into consideration the geometry of each one. Obviously, the geometry of each of these images is a consequence of the geometry of the sensor's mirror used. This tech ...

2005

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Daniel Gatica-Perez, Jean-Marc Odobez, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas

We present a novel approach for contextual segmentation of complex visual scenes, based on the use of bags of local invariant features (visterms) and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that specific le ...

IDIAP2005

Coevolution of active vision and feature selection

Dario Floreano, Eric Sauser, Toshifumi Kato, Davide Marocco

We show that complex visual tasks, such as position- and size-invariant shape recognition and navigation in the environment, can be tackled with simple architectures generated by a coevolutionary process of active vision and feature selection. Behavioral m ...

2004

Feature point extraction using scale-space representation

Touradj Ebrahimi, Yousri Abdeljaoued

An algorithm for feature point extraction is presented. It is based on a scale-space representation of the image as well as a system for tracking across scales. Using synthetic and real images, it is shown that the proposed algorithm produces stable and we ...

2004

OmniSIFT: Scale Invariant Features in Omnidirectional Images

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Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Optimal control of geodesics in Riemannian manifolds

Scale-space analysis and active contours for omnidirectional images

Orientation histogram-based matching for Region Tracking

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Laplacian Operator, Diffusion Flow and Active Contour on non-Euclidean Images

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Coevolution of active vision and feature selection

Feature point extraction using scale-space representation

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Optimal control of geodesics in Riemannian manifolds

Laplacian Operator, Diffusion Flow and Active Contour on non-Euclidean Images

Coevolution of active vision and feature selection

Scale-space analysis and active contours for omnidirectional images

Feature point extraction using scale-space representation

Orientation histogram-based matching for Region Tracking

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Integrating co-occurrence and spatial contexts on patch-based scene segmentation