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Author | Cristhian A. Aguilera-Carrasco | ||||
Title | Evaluation of feature detectors and descriptors in VISIBLE-LWIR cross-spectral imaging | Type | Report | ||
Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 177 | Issue | Pages | ||
Keywords | Multi-spectral; Cross-spectral; Visible-LWIR imaging; Multimodal. | ||||
Abstract | This thesis evaluates the performance of different state-of-art feature detectors and descriptors algorithms in the Visible-LWIR cross-spectral scenario. The focus is to determine if current detector and descriptor algorithms can be used to match features between the LWIR spectrum and the visible spectrum in applications such as, visual odometry, object recognition, image registration and stereo vision. An outdoor cross-spectral dataset was created to evaluate the suitability of the different algorithms. The results
show that the tested algorithms are not suitable to the task of matching features across different spectra. The repeatability ratio was smaller than the 30 percent in the best case and in general matched features were not accurate located. Additionally, these results also suggest that is necessary to create new algorithms that take into account the nature of the different spectra, describing characteristics that exist in both spectra such as discontinuities. |
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Corporate Author | Thesis | Master's thesis | |||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @Agu2014 | Serial | 2526 | ||
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Author | Francisco Blanco; Felipe Lumbreras; Joan Serrat; Roswitha Siener; Silvia Serranti; Giuseppe Bonifazi; Montserrat Lopez Mesas; Manuel Valiente | ||||
Title | Taking advantage of Hyperspectral Imaging classification of urinary stones against conventional IR Spectroscopy | Type | Journal Article | ||
Year | 2014 | Publication | Journal of Biomedical Optics | Abbreviated Journal | JBiO |
Volume | 19 | Issue | 12 | Pages | 126004-1 - 126004-9 |
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Abstract | The analysis of urinary stones is mandatory for the best management of the disease after the stone passage in order to prevent further stone episodes. Thus the use of an appropriate methodology for an individualized stone analysis becomes a key factor for giving the patient the most suitable treatment. A recently developed hyperspectral imaging methodology, based on pixel-to-pixel analysis of near-infrared spectral images, is compared to the reference technique in stone analysis, infrared (IR) spectroscopy. The developed classification model yields >90% correct classification rate when compared to IR and is able to precisely locate stone components within the structure of the stone with a 15 µm resolution. Due to the little sample pretreatment, low analysis time, good performance of the model, and the automation of the measurements, they become analyst independent; this methodology can be considered to become a routine analysis for clinical laboratories. | ||||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ BLS2014 | Serial | 2563 | ||
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Author | Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez | ||||
Title | 3d Pedestrian Detection via Random Forest | Type | Miscellaneous | ||
Year | 2014 | Publication | European Conference on Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 231-238 | ||
Keywords | Pedestrian Detection | ||||
Abstract | Our demo focuses on showing the extraordinary performance of our novel 3D pedestrian detector along with its simplicity and real-time capabilities. This detector has been designed for autonomous driving applications, but it can also be applied in other scenarios that cover both outdoor and indoor applications.
Our pedestrian detector is based on the combination of a random forest classifier with HOG-LBP features and the inclusion of a preprocessing stage based on 3D scene information in order to precisely determinate the image regions where the detector should search for pedestrians. This approach ends up in a high accurate system that runs real-time as it is required by many computer vision and robotics applications. |
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Address | Zurich; suiza; September 2014 | ||||
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Area | Expedition | Conference | ECCV-Demo | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ VRR2014 | Serial | 2570 | ||
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Author | Sebastian Ramos | ||||
Title | Vision-based Detection of Road Hazards for Autonomous Driving | Type | Report | ||
Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
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Address | UAB; September 2014 | ||||
Corporate Author | Thesis | Master's thesis | |||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ Ram2014 | Serial | 2580 | ||
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Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
Title | Domain Adaptation of Deformable Part-Based Models | Type | Journal Article | ||
Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 36 | Issue | 12 | Pages | 2367-2380 |
Keywords | Domain Adaptation; Pedestrian Detection | ||||
Abstract | The accuracy of object classifiers can significantly drop when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, adapting the classifiers to the scenario in which they must operate is of paramount importance. We present novel domain adaptation (DA) methods for object detection. As proof of concept, we focus on adapting the state-of-the-art deformable part-based model (DPM) for pedestrian detection. We introduce an adaptive structural SVM (A-SSVM) that adapts a pre-learned classifier between different domains. By taking into account the inherent structure in feature space (e.g., the parts in a DPM), we propose a structure-aware A-SSVM (SA-SSVM). Neither A-SSVM nor SA-SSVM needs to revisit the source-domain training data to perform the adaptation. Rather, a low number of target-domain training examples (e.g., pedestrians) are used. To address the scenario where there are no target-domain annotated samples, we propose a self-adaptive DPM based on a self-paced learning (SPL) strategy and a Gaussian Process Regression (GPR). Two types of adaptation tasks are assessed: from both synthetic pedestrians and general persons (PASCAL VOC) to pedestrians imaged from an on-board camera. Results show that our proposals avoid accuracy drops as high as 15 points when comparing adapted and non-adapted detectors. | ||||
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Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 0162-8828 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.057; 600.054; 601.217; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ XRV2014b | Serial | 2436 | ||
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Author | Jiaolong Xu; Sebastian Ramos;David Vazquez; Antonio Lopez | ||||
Title | Cost-sensitive Structured SVM for Multi-category Domain Adaptation | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 3886 - 3891 | ||
Keywords | Domain Adaptation; Pedestrian Detection | ||||
Abstract | Domain adaptation addresses the problem of accuracy drop that a classifier may suffer when the training data (source domain) and the testing data (target domain) are drawn from different distributions. In this work, we focus on domain adaptation for structured SVM (SSVM). We propose a cost-sensitive domain adaptation method for SSVM, namely COSS-SSVM. In particular, during the re-training of an adapted classifier based on target and source data, the idea that we explore consists in introducing a non-zero cost even for correctly classified source domain samples. Eventually, we aim to learn a more targetoriented classifier by not rewarding (zero loss) properly classified source-domain training samples. We assess the effectiveness of COSS-SSVM on multi-category object recognition. | ||||
Address | Stockholm; Sweden; August 2014 | ||||
Corporate Author | Thesis | ||||
Publisher | IEEE | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | ADAS; 600.057; 600.054; 601.217; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ XRV2014a | Serial | 2434 | ||
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Author | David Vazquez; Javier Marin; Antonio Lopez; Daniel Ponsa; David Geronimo | ||||
Title | Virtual and Real World Adaptation for Pedestrian Detection | Type | Journal Article | ||
Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 36 | Issue | 4 | Pages | 797-809 |
Keywords | Domain Adaptation; Pedestrian Detection | ||||
Abstract | Pedestrian detection is of paramount interest for many applications. Most promising detectors rely on discriminatively learnt classifiers, i.e., trained with annotated samples. However, the annotation step is a human intensive and subjective task worth to be minimized. By using virtual worlds we can automatically obtain precise and rich annotations. Thus, we face the question: can a pedestrian appearance model learnt in realistic virtual worlds work successfully for pedestrian detection in realworld images?. Conducted experiments show that virtual-world based training can provide excellent testing accuracy in real world, but it can also suffer the dataset shift problem as real-world based training does. Accordingly, we have designed a domain adaptation framework, V-AYLA, in which we have tested different techniques to collect a few pedestrian samples from the target domain (real world) and combine them with the many examples of the source domain (virtual world) in order to train a domain adapted pedestrian classifier that will operate in the target domain. V-AYLA reports the same detection accuracy than when training with many human-provided pedestrian annotations and testing with real-world images of the same domain. To the best of our knowledge, this is the first work demonstrating adaptation of virtual and real worlds for developing an object detector. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 0162-8828 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.057; 600.054; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ VML2014 | Serial | 2275 | ||
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Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
Title | Incremental Domain Adaptation of Deformable Part-based Models | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Pedestrian Detection; Part-based models; Domain Adaptation | ||||
Abstract | Nowadays, classifiers play a core role in many computer vision tasks. The underlying assumption for learning classifiers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classifiers. However, in practice, there are different reasons that can break this constancy assumption. Accordingly, reusing existing classifiers by adapting them from the previous training environment (source domain) to the new testing one (target domain)
is an approach with increasing acceptance in the computer vision community. In this paper we focus on the domain adaptation of deformable part-based models (DPMs) for object detection. In particular, we focus on a relatively unexplored scenario, i.e. incremental domain adaptation for object detection assuming weak-labeling. Therefore, our algorithm is ready to improve existing source-oriented DPM-based detectors as soon as a little amount of labeled target-domain training data is available, and keeps improving as more of such data arrives in a continuous fashion. For achieving this, we follow a multiple instance learning (MIL) paradigm that operates in an incremental per-image basis. As proof of concept, we address the challenging scenario of adapting a DPM-based pedestrian detector trained with synthetic pedestrians to operate in real-world scenarios. The obtained results show that our incremental adaptive models obtain equally good accuracy results as the batch learned models, while being more flexible for handling continuously arriving target-domain data. |
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Address | Nottingham; uk; September 2014 | ||||
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Publisher | BMVA Press | Place of Publication | Editor | Valstar, Michel and French, Andrew and Pridmore, Tony | |
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Area | Expedition | Conference | BMVC | ||
Notes | ADAS; 600.057; 600.054; 600.076 | Approved | no | ||
Call Number | XRV2014c; ADAS @ adas @ xrv2014c | Serial | 2455 | ||
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Author | P. Ricaurte; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
Title | Performance Evaluation of Feature Point Descriptors in the Infrared Domain | Type | Conference Article | ||
Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 545-550 | |
Keywords | Infrared Imaging; Feature Point Descriptors | ||||
Abstract | This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. | ||||
Address | Lisboa; Portugal; January 2014 | ||||
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Area | Expedition | Conference | VISAPP | ||
Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RCA2014b | Serial | 2476 | ||
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Author | Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
Title | Cross-spectral Stereo Correspondence using Dense Flow Fields | Type | Conference Article | ||
Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 3 | Issue | Pages | 613-617 | |
Keywords | Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum | ||||
Abstract | This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach. | ||||
Address | Lisboa; Portugal; January 2014 | ||||
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Area | Expedition | Conference | VISAPP | ||
Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OAV2014 | Serial | 2477 | ||
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Author | Mohammad Rouhani; E. Boyer; Angel Sappa | ||||
Title | Non-Rigid Registration meets Surface Reconstruction | Type | Conference Article | ||
Year | 2014 | Publication | International Conference on 3D Vision | Abbreviated Journal | |
Volume | Issue | Pages | 617-624 | ||
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Abstract | Non rigid registration is an important task in computer vision with many applications in shape and motion modeling. A fundamental step of the registration is the data association between the source and the target sets. Such association proves difficult in practice, due to the discrete nature of the information and its corruption by various types of noise, e.g. outliers and missing data. In this paper we investigate the benefit of the implicit representations for the non-rigid registration of 3D point clouds. First, the target points are described with small quadratic patches that are blended through partition of unity weighting. Then, the discrete association between the source and the target can be replaced by a continuous distance field induced by the interface. By combining this distance field with a proper deformation term, the registration energy can be expressed in a linear least square form that is easy and fast to solve. This significantly eases the registration by avoiding direct association between points. Moreover, a hierarchical approach can be easily implemented by employing coarse-to-fine representations. Experimental results are provided for point clouds from multi-view data sets. The qualitative and quantitative comparisons show the outperformance and robustness of our framework. %in presence of noise and outliers. | ||||
Address | Tokyo; Japan; December 2014 | ||||
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Area | Expedition | Conference | 3DV | ||
Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RBS2014 | Serial | 2534 | ||
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Author | Joan Marc Llargues Asensio; Juan Peralta; Raul Arrabales; Manuel Gonzalez Bedia; Paulo Cortez; Antonio Lopez | ||||
Title | Artificial Intelligence Approaches for the Generation and Assessment of Believable Human-Like Behaviour in Virtual Characters | Type | Journal Article | ||
Year | 2014 | Publication | Expert Systems With Applications | Abbreviated Journal | EXSY |
Volume | 41 | Issue | 16 | Pages | 7281–7290 |
Keywords | Turing test; Human-like behaviour; Believability; Non-player characters; Cognitive architectures; Genetic algorithm; Artificial neural networks | ||||
Abstract | Having artificial agents to autonomously produce human-like behaviour is one of the most ambitious original goals of Artificial Intelligence (AI) and remains an open problem nowadays. The imitation game originally proposed by Turing constitute a very effective method to prove the indistinguishability of an artificial agent. The behaviour of an agent is said to be indistinguishable from that of a human when observers (the so-called judges in the Turing test) cannot tell apart humans and non-human agents. Different environments, testing protocols, scopes and problem domains can be established to develop limited versions or variants of the original Turing test. In this paper we use a specific version of the Turing test, based on the international BotPrize competition, built in a First-Person Shooter video game, where both human players and non-player characters interact in complex virtual environments. Based on our past experience both in the BotPrize competition and other robotics and computer game AI applications we have developed three new more advanced controllers for believable agents: two based on a combination of the CERA–CRANIUM and SOAR cognitive architectures and other based on ADANN, a system for the automatic evolution and adaptation of artificial neural networks. These two new agents have been put to the test jointly with CCBot3, the winner of BotPrize 2010 competition (Arrabales et al., 2012), and have showed a significant improvement in the humanness ratio. Additionally, we have confronted all these bots to both First-person believability assessment (BotPrize original judging protocol) and Third-person believability assessment, demonstrating that the active involvement of the judge has a great impact in the recognition of human-like behaviour. | ||||
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Notes | ADAS; 600.055; 600.057; 600.076 | Approved | no | ||
Call Number | Admin @ si @ LPA2014 | Serial | 2500 | ||
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Author | Onur Ferhat; Fernando Vilariño; F. Javier Sanchez | ||||
Title | A cheap portable eye-tracker solution for common setups. | Type | Journal Article | ||
Year | 2014 | Publication | Journal of Eye Movement Research | Abbreviated Journal | JEMR |
Volume | 7 | Issue | 3 | Pages | 1-10 |
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Abstract | We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system which can work on a computer with 30Hz sampling rate. After assessing the accuracy of our eye-tracker in elaborated experiments involving 12 subjects under 4 different system setups, we install it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.42° horizontal accuracy with 3Hz refresh rate for a building cost of 70 Euros. | ||||
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Notes | ;SIAI | Approved | no | ||
Call Number | Admin @ si @ FVS2014 | Serial | 2435 | ||
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