The Experts below are selected from a list of 87 Experts worldwide ranked by ideXlab platform
Eckehard Steinbach - One of the best experts on this subject based on the ideXlab platform.
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virtual Reference View generation for cbir based visual pose estimation
ACM Multimedia, 2012Co-Authors: Robert Huitl, Georg Schroth, Sebastian Hilsenbeck, Florian Schweiger, Eckehard SteinbachAbstract:Determining the pose of a mobile device based on visual information is a promising approach to solve the indoor localization problem. We present an approach that transforms localized images along a mapping trajectory into virtual Viewpoints that cover a set of densely sampled camera positions and orientations in a confined environment. The Viewpoints are represented by their respective bag-of-features vectors and image retrieval techniques are applied to determine the most likely pose of query images at very low computational complexity. As virtual image locations and orientations are decoupled from actual image locations, the system is able to work with sparse Reference imagery and copes well with perspective distortion. Experiments confirm that pose retrieval performance is significantly improved.
Beatrice Pesquetpopescu - One of the best experts on this subject based on the ideXlab platform.
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Reference View selection in dibr based multiView coding
IEEE Transactions on Image Processing, 2016Co-Authors: Thomas Maugey, Giovanni Petrazzuoli, Pascal Frossard, Marco Cagnazzo, Beatrice PesquetpopescuAbstract:Augmented reality, interactive navigation in 3D scenes, multiView video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant increase in the number of images in multiView systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multiView video compression strategies have been proposed recently. Most of them use the concept of Reference or key Views that are used to estimate other images when there is high correlation in the data set. In such coding schemes, the two following questions become fundamental: 1) how many Reference Views have to be chosen for keeping a good reconstruction quality under coding cost constraints? And 2) where to place these key Views in the multiView data set? As these questions are largely overlooked in the literature, we study the Reference View selection problem and propose an algorithm for the optimal selection of Reference Views in multiView coding systems. Based on a novel metric that measures the similarity between the Views, we formulate an optimization problem for the positioning of the Reference Views, such that both the distortion of the View reconstruction and the coding rate cost are minimized. We solve this new problem with a shortest path algorithm that determines both the optimal number of Reference Views and their positions in the image set. We experimentally validate our solution in a practical multiView distributed coding system and in the standardized 3D-HEVC multiView coding scheme. We show that considering the 3D scene geometry in the Reference View, positioning problem brings significant rate–distortion improvements and outperforms the traditional coding strategy that simply selects key frames based on the distance between cameras.
Robert Huitl - One of the best experts on this subject based on the ideXlab platform.
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virtual Reference View generation for cbir based visual pose estimation
ACM Multimedia, 2012Co-Authors: Robert Huitl, Georg Schroth, Sebastian Hilsenbeck, Florian Schweiger, Eckehard SteinbachAbstract:Determining the pose of a mobile device based on visual information is a promising approach to solve the indoor localization problem. We present an approach that transforms localized images along a mapping trajectory into virtual Viewpoints that cover a set of densely sampled camera positions and orientations in a confined environment. The Viewpoints are represented by their respective bag-of-features vectors and image retrieval techniques are applied to determine the most likely pose of query images at very low computational complexity. As virtual image locations and orientations are decoupled from actual image locations, the system is able to work with sparse Reference imagery and copes well with perspective distortion. Experiments confirm that pose retrieval performance is significantly improved.
Thomas Maugey - One of the best experts on this subject based on the ideXlab platform.
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Reference View selection in dibr based multiView coding
IEEE Transactions on Image Processing, 2016Co-Authors: Thomas Maugey, Giovanni Petrazzuoli, Pascal Frossard, Marco Cagnazzo, Beatrice PesquetpopescuAbstract:Augmented reality, interactive navigation in 3D scenes, multiView video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant increase in the number of images in multiView systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multiView video compression strategies have been proposed recently. Most of them use the concept of Reference or key Views that are used to estimate other images when there is high correlation in the data set. In such coding schemes, the two following questions become fundamental: 1) how many Reference Views have to be chosen for keeping a good reconstruction quality under coding cost constraints? And 2) where to place these key Views in the multiView data set? As these questions are largely overlooked in the literature, we study the Reference View selection problem and propose an algorithm for the optimal selection of Reference Views in multiView coding systems. Based on a novel metric that measures the similarity between the Views, we formulate an optimization problem for the positioning of the Reference Views, such that both the distortion of the View reconstruction and the coding rate cost are minimized. We solve this new problem with a shortest path algorithm that determines both the optimal number of Reference Views and their positions in the image set. We experimentally validate our solution in a practical multiView distributed coding system and in the standardized 3D-HEVC multiView coding scheme. We show that considering the 3D scene geometry in the Reference View, positioning problem brings significant rate–distortion improvements and outperforms the traditional coding strategy that simply selects key frames based on the distance between cameras.
Florian Schweiger - One of the best experts on this subject based on the ideXlab platform.
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virtual Reference View generation for cbir based visual pose estimation
ACM Multimedia, 2012Co-Authors: Robert Huitl, Georg Schroth, Sebastian Hilsenbeck, Florian Schweiger, Eckehard SteinbachAbstract:Determining the pose of a mobile device based on visual information is a promising approach to solve the indoor localization problem. We present an approach that transforms localized images along a mapping trajectory into virtual Viewpoints that cover a set of densely sampled camera positions and orientations in a confined environment. The Viewpoints are represented by their respective bag-of-features vectors and image retrieval techniques are applied to determine the most likely pose of query images at very low computational complexity. As virtual image locations and orientations are decoupled from actual image locations, the system is able to work with sparse Reference imagery and copes well with perspective distortion. Experiments confirm that pose retrieval performance is significantly improved.