Publications by Engin Tola | EPFL Graph Search

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Stereo reconstruction is a fundamental problem of computer vision. It has been studied for more than three decades and significant progress has been made in recent years as evidenced by the quality of the models now being produced. This is highly related w ...

We introduce a novel local image descriptor designed for dense wide-baseline matching purposes. We feed our descriptors to a graph-cuts based dense depth map estimation algorithm and this yields better wide-baseline performance than the commonly used corre ...

We present a new approach for large scale multi-view stereo matching, which is designed to operate on ultra high resolution image sets and efficiently compute dense 3D point clouds. We show that, by using a robust descriptor for matching purposes and high ...

It has recently been shown that deformable 3D surfaces could be recovered from single video streams. However, existing techniques either require a reference view in which the shape of the surface is known a priori, which often may not be available, or requ ...

Dense disparity maps can be computed from wide-baseline stereo pairs but will inevitably contain large areas where the depth cannot be estimated accurately because the pixels are seen in one view only. A traditional approach to this problem is to introduce ...

In this paper, we introduce a local image descriptor, DAISY, which is very efficient to compute densely. We also present an EM based algorithm to compute dense depth and occlusion maps from wide baseline image pairs using this descriptor. This yields much ...

Engin Tola

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DAISY: A Fast Descriptor for Dense Wide Baseline Stereo and Multiview Reconstruction

A fast local descriptor for dense matching

Efficient Large Scale Multi-View Stereo for Ultra High Resolution Image Sets

Template-Free Monocular Reconstruction of Deformable Surfaces

Large occlusion completion using normal maps

Daisy: An Efficient Dense Descriptor Applied to Wide Baseline Stereo