Towards precise outdoor localisation based on image recognition

In recent years significant progress has been made in the field of visual search, mostly due to the introduction of powerful local image features. At the same time, a rapid development of mobile platforms enabled deployment of image retrieval systems on mobile devices. Various mobile applications of the visual search have been proposed, one of the most interesting being geo-localization service based on image recognition and other positioning information. This thesis attempts to advance the existing visual search system developed at Telefonica I+D Barcelona so it could be used for high precision geo-localization. In order to do so, this dissertation tackles two significant challenges of image retrieval: improvement in robustness of the detection of similarities between images and increase of discriminatory power. The work advances the state-of-the-art with three main contributions. The first contribution consists of the development of an evaluation framework for visual search engine. Since the assessment of any complex system is crucial for its development and analysis, an exhaustive set of evaluation measures is selected from the relevant literature and implemented. Furthermore, several datasets along with the corresponding information about correct correspondences between the images have been gathered and unified. The second contribution considers the representation of image features describing salient regions and attempts to alleviate the quantization effects introduced during its creation. A mechanism that in the literature is commonly referred to as soft assignment is adapted to a visual search engine of Telefonica I+D with several extensions. The third and final contribution consists of a post-processing stage that increases discriminative power by verification of local correspondences' spatial layout. The performance and generality of the proposed solutions has been analyzed based on extensive evaluation using the framework proposed in this work

Plugin Networks for Inference under Partial Evidence

In this paper, we propose a novel method to incorporate partial evidence in the inference of deep convolutional neural networks. Contrary to the existing, top performing methods, which either iteratively modify the input of the network or exploit external label taxonomy to take the partial evidence into account, we add separate network modules ("Plugin Networks") to the intermediate layers of a pre-trained convolutional network. The goal of these modules is to incorporate additional signal, ie information about known labels, into the inference procedure and adjust the predicted output accordingly. Since the attached plugins have a simple structure, consisting of only fully connected layers, we drastically reduced the computational cost of training and inference. At the same time, the proposed architecture allows to propagate information about known labels directly to the intermediate layers to improve the final representation. Extensive evaluation of the proposed method confirms that our Plugin Networks outperform the state-of-the-art in a variety of tasks, including scene categorization, multi-label image annotation, and semantic segmentation.Comment: Accepted to WACV 202

Monitoring Achilles tendon healing progress in ultrasound imaging with convolutional neural networks

Achilles tendon rupture is a debilitating injury, which is typically treated with surgical repair and long-term rehabilitation. The recovery, however, is protracted and often incomplete. Diagnosis, as well as healing progress assessment, are largely based on ultrasound and magnetic resonance imaging. In this paper, we propose an automatic method based on deep learning for analysis of Achilles tendon condition and estimation of its healing progress on ultrasound images. We develop custom convolutional neural networks for classification and regression on healing score and feature extraction. Our models are trained and validated on an acquired dataset of over 250.000 sagittal and over 450.000 axial ultrasound slices. The obtained estimates show a high correlation with the assessment of expert radiologists, with respect to all key parameters describing healing progress. We also observe that parameters associated with i.a. intratendinous healing processes are better modeled with sagittal slices. We prove that ultrasound imaging is quantitatively useful for clinical assessment of Achilles tendon healing process and should be viewed as complementary to magnetic resonance imaging.Comment: Paper accepted to MICCAI'19 SUSI worksho

Towards precise outdoor localisation based on image recognition

In recent years significant progress has been made in the field of visual search, mostly due to the introduction of powerful local image features. At the same time, a rapid development of mobile platforms enabled deployment of image retrieval systems on mobile devices. Various mobile applications of the visual search have been proposed, one of the most interesting being geo-localization service based on image recognition and other positioning information. This thesis attempts to advance the existing visual search system developed at Telefonica I+D Barcelona so it could be used for high precision geo-localization. In order to do so, this dissertation tackles two significant challenges of image retrieval: improvement in robustness of the detection of similarities between images and increase of discriminatory power. The work advances the state-of-the-art with three main contributions. The first contribution consists of the development of an evaluation framework for visual search engine. Since the assessment of any complex system is crucial for its development and analysis, an exhaustive set of evaluation measures is selected from the relevant literature and implemented. Furthermore, several datasets along with the corresponding information about correct correspondences between the images have been gathered and unified. The second contribution considers the representation of image features describing salient regions and attempts to alleviate the quantization effects introduced during its creation. A mechanism that in the literature is commonly referred to as soft assignment is adapted to a visual search engine of Telefonica I+D with several extensions. The third and final contribution consists of a post-processing stage that increases discriminative power by verification of local correspondences' spatial layout. The performance and generality of the proposed solutions has been analyzed based on extensive evaluation using the framework proposed in this work

Towards precise outdoor localisation based on image recognition

In recent years significant progress has been made in the field of visual search, mostly due to the introduction of powerful local image features. At the same time, a rapid development of mobile platforms enabled deployment of image retrieval systems on mobile devices. Various mobile applications of the visual search have been proposed, one of the most interesting being geo-localization service based on image recognition and other positioning information. This thesis attempts to advance the existing visual search system developed at Telefonica I+D Barcelona so it could be used for high precision geo-localization. In order to do so, this dissertation tackles two significant challenges of image retrieval: improvement in robustness of the detection of similarities between images and increase of discriminatory power. The work advances the state-of-the-art with three main contributions. The first contribution consists of the development of an evaluation framework for visual search engine. Since the assessment of any complex system is crucial for its development and analysis, an exhaustive set of evaluation measures is selected from the relevant literature and implemented. Furthermore, several datasets along with the corresponding information about correct correspondences between the images have been gathered and unified. The second contribution considers the representation of image features describing salient regions and attempts to alleviate the quantization effects introduced during its creation. A mechanism that in the literature is commonly referred to as soft assignment is adapted to a visual search engine of Telefonica I+D with several extensions. The third and final contribution consists of a post-processing stage that increases discriminative power by verification of local correspondences' spatial layout. The performance and generality of the proposed solutions has been analyzed based on extensive evaluation using the framework proposed in this work

Multiplicity dependence of light (anti-)nuclei production in p–Pb collisions at sNN=5.02 TeV

The measurement of the deuteron and anti-deuteron production in the rapidity range −1 < y < 0 as a function of transverse momentum and event multiplicity in p–Pb collisions at √sNN = 5.02 TeV is presented. (Anti-)deuterons are identified via their specific energy loss dE/dx and via their time-of- flight. Their production in p–Pb collisions is compared to pp and Pb–Pb collisions and is discussed within the context of thermal and coalescence models. The ratio of integrated yields of deuterons to protons (d/p) shows a significant increase as a function of the charged-particle multiplicity of the event starting from values similar to those observed in pp collisions at low multiplicities and approaching those observed in Pb–Pb collisions at high multiplicities. The mean transverse particle momenta are extracted from the deuteron spectra and the values are similar to those obtained for p and particles. Thus, deuteron spectra do not follow mass ordering. This behaviour is in contrast to the trend observed for non-composite particles in p–Pb collisions. In addition, the production of the rare 3He and 3He nuclei has been studied. The spectrum corresponding to all non-single diffractive p-Pb collisions is obtained in the rapidity window −1 < y < 0 and the pT-integrated yield dN/dy is extracted. It is found that the yields of protons, deuterons, and 3He, normalised by the spin degeneracy factor, follow an exponential decrease with mass number

Measurement of the inclusive isolated-photon production cross section in pp and Pb−-Pb collisions at sNN=5.02\sqrt{s_{\rm NN}}=5.02 TeV

International audienceThe ALICE Collaboration at the CERN LHC has measured the inclusive production cross section of isolated photons at midrapidity as a function of the photon transverse momentum ($p_{\rm T}^{\gamma}$), in Pb-Pb collisions in different centrality intervals, and in pp collisions, at centre-of-momentum energy per nucleon pair of $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV. The photon transverse momentum range is between 10-14 and 40-140 GeV/$c$, depending on the collision system and on the Pb-Pb centrality class. The result extends to lower $p_{\rm T}^{\gamma}$ than previously published results by the ATLAS and CMS experiments at the same collision energy. The covered pseudorapidity range is $|\eta^{\gamma}| <0.67$. The isolation selection is based on a charged particle isolation momentum threshold $p_{\rm T}^{\rm iso,~ch} = 1.5$ GeV/$c$ within a cone of radii $R=0.2$ and $0.4$. The nuclear modification factor is calculated and found to be consistent with unity in all centrality classes, and also consistent with the HG-PYTHIA model, which describes the event selection and geometry biases that affect the centrality determination in peripheral Pb-Pb collisions. The measurement is compared to next-to-leading order perturbative QCD calculations and to the measurements of isolated photons and Z$^0$ bosons from the CMS experiment, which are all found to be in agreement

Measurement of the inclusive isolated-photon production cross section in pp and Pb−-Pb collisions at sNN=5.02\sqrt{s_{\rm NN}}=5.02 TeV

International audienceThe ALICE Collaboration at the CERN LHC has measured the inclusive production cross section of isolated photons at midrapidity as a function of the photon transverse momentum ($p_{\rm T}^{\gamma}$), in Pb-Pb collisions in different centrality intervals, and in pp collisions, at centre-of-momentum energy per nucleon pair of $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV. The photon transverse momentum range is between 10-14 and 40-140 GeV/$c$, depending on the collision system and on the Pb-Pb centrality class. The result extends to lower $p_{\rm T}^{\gamma}$ than previously published results by the ATLAS and CMS experiments at the same collision energy. The covered pseudorapidity range is $|\eta^{\gamma}| <0.67$. The isolation selection is based on a charged particle isolation momentum threshold $p_{\rm T}^{\rm iso,~ch} = 1.5$ GeV/$c$ within a cone of radii $R=0.2$ and $0.4$. The nuclear modification factor is calculated and found to be consistent with unity in all centrality classes, and also consistent with the HG-PYTHIA model, which describes the event selection and geometry biases that affect the centrality determination in peripheral Pb-Pb collisions. The measurement is compared to next-to-leading order perturbative QCD calculations and to the measurements of isolated photons and Z$^0$ bosons from the CMS experiment, which are all found to be in agreement