LDAHash: Improved Matching with Smaller Descriptors
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Two classical but crucial and unsolved problems in Computer Vision are treated in this thesis: tracking and matching. The first part of the thesis deals with tracking, studying two of its main difficulties: object representation model drift and total occlu ...
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 ...
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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 ...
With the increasing demand of information for more immersive applications such as Google Street view or 3D movies, the efficient analysis of visual data from cameras has gained more importance. This visual information permits to extract some crucial inform ...
We propose a method to compute scale invariant features in omnidirectional images. We present a formulation based on Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that describe the mirror and lens structure in ...
SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition, photo-tourism and 3D reconstruction. Feature descriptors can be designed to b ...
Technological solutions for obstacle-detection systems have been proposed to prevent accidents in safety-transport applications. In order to avoid the limits of these proposed technologies, an obstacle-detection system utilizing stereo cameras is proposed ...
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 ...
Most of the multi-camera systems assume a well structured environment to detect and match objects across cameras. Cameras need to be fixed and calibrated. In this work, a novel system is presented to detect and match any objects in a network of uncalibrate ...
In this paper, we consider the problem of speaker verification as a two-class object detection problem in computer vision, where the object instances are 1-D short-time spectral vectors obtained from the speech signal. More precisely, we investigate the ge ...
