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| Author | Joost Van de Weijer; Fahad Shahbaz Khan | ||||
| Title | An Overview of Color Name Applications in Computer Vision | Type | Conference Article | ||
| Year | 2015 | Publication | Computational Color Imaging Workshop | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | color features; color names; object recognition | ||||
| Abstract | In this article we provide an overview of color name applications in computer vision. Color names are linguistic labels which humans use to communicate color. Computational color naming learns a mapping from pixels values to color names. In recent years color names have been applied to a wide variety of computer vision applications, including image classification, object recognition, texture classification, visual tracking and action recognition. Here we provide an overview of these results which show that in general color names outperform photometric invariants as a color representation. | ||||
| Address | Saint Etienne; France; March 2015 | ||||
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| Area | Expedition | Conference | CCIW | ||
| Notes | LAMP; 600.079; 600.068 | Approved | no | ||
| Call Number | Admin @ si @ WeK2015 | Serial | 2586 | ||
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| Author | Wenjuan Gong; Y.Huang; Jordi Gonzalez; Liang Wang | ||||
| Title | An Effective Solution to Double Counting Problem in Human Pose Estimation | Type | Miscellaneous | ||
| Year | 2015 | Publication | Arxiv | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Pose estimation; double counting problem; mix-ture of parts Model | ||||
| Abstract | The mixture of parts model has been successfully applied to solve the 2D
human pose estimation problem either as an explicitly trained body part model or as latent variables for pedestrian detection. Even in the era of massive applications of deep learning techniques, the mixture of parts model is still effective in solving certain problems, especially in the case with limited numbers of training samples. In this paper, we consider using the mixture of parts model for pose estimation, wherein a tree structure is utilized for representing relations between connected body parts. This strategy facilitates training and inferencing of the model but suffers from double counting problems, where one detected body part is counted twice due to lack of constrains among unconnected body parts. To solve this problem, we propose a generalized solution in which various part attributes are captured by multiple features so as to avoid the double counted problem. Qualitative and quantitative experimental results on a public available dataset demonstrate the effectiveness of our proposed method. An Effective Solution to Double Counting Problem in Human Pose Estimation – ResearchGate. Available from: http://www.researchgate.net/publication/271218491AnEffectiveSolutiontoDoubleCountingProbleminHumanPose_Estimation [accessed Oct 22, 2015]. |
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| Notes | ISE; 600.078 | Approved | no | ||
| Call Number | Admin @ si @ GHG2015 | Serial | 2590 | ||
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| Author | Adriana Romero; Nicolas Ballas; Samira Ebrahimi Kahou; Antoine Chassang; Carlo Gatta; Yoshua Bengio | ||||
| Title | FitNets: Hints for Thin Deep Nets | Type | Conference Article | ||
| Year | 2015 | Publication | 3rd International Conference on Learning Representations ICLR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Computer Science ; Learning; Computer Science ;Neural and Evolutionary Computing | ||||
| Abstract | While depth tends to improve network performances, it also makes gradient-based training more difficult since deeper networks tend to be more non-linear. The recently proposed knowledge distillation approach is aimed at obtaining small and fast-to-execute models, and it has shown that a student network could imitate the soft output of a larger teacher network or ensemble of networks. In this paper, we extend this idea to allow the training of a student that is deeper and thinner than the teacher, using not only the outputs but also the intermediate representations learned by the teacher as hints to improve the training process and final performance of the student. Because the student intermediate hidden layer will generally be smaller than the teacher's intermediate hidden layer, additional parameters are introduced to map the student hidden layer to the prediction of the teacher hidden layer. This allows one to train deeper students that can generalize better or run faster, a trade-off that is controlled by the chosen student capacity. For example, on CIFAR-10, a deep student network with almost 10.4 times less parameters outperforms a larger, state-of-the-art teacher network. | ||||
| Address | San Diego; CA; May 2015 | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICLR | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ RBK2015 | Serial | 2593 | ||
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| Author | Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika | ||||
| Title | Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics | Type | Conference Article | ||
| Year | 2014 | Publication | 1st Workshop on Computer Vision for Affective Computing | Abbreviated Journal | |
| Volume | Issue | Pages | 1-8 | ||
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| Abstract | Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this paper, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, view- and texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression. |
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| Address | Singapore; November 2014 | ||||
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| Area | Expedition | Conference | ACCV | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RBD2014 | Serial | 2599 | ||
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| Author | C. Alejandro Parraga | ||||
| Title | Perceptual Psychophysics | Type | Book Chapter | ||
| Year | 2015 | Publication | Biologically-Inspired Computer Vision: Fundamentals and Applications | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | G.Cristobal; M.Keil; L.Perrinet | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-527-41264-8 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | CIC; 600.074 | Approved | no | ||
| Call Number | Admin @ si @ Par2015 | Serial | 2600 | ||
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| Author | Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell | ||||
| Title | Quasi-real time digital assessment of Central Airway Obstruction | Type | Conference Article | ||
| Year | 2015 | Publication | 3rd European congress for bronchology and interventional pulmonology ECBIP2015 | Abbreviated Journal | |
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| Address | Barcelona; Spain; April 2015 | ||||
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| Area | Expedition | Conference | ECBIP | ||
| Notes | IAM; MV; 600.075 | Approved | no | ||
| Call Number | SGT2015 | Serial | 2612 | ||
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| Author | Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell; Debora Gil | ||||
| Title | Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy | Type | Conference Article | ||
| Year | 2015 | Publication | 6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015 | Abbreviated Journal | |
| Volume | 10 | Issue | 6 | Pages | 935-945 |
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| Abstract | PURPOSE:
Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service. METHODS: Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion. RESULTS: Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room. CONCLUSIONS: Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done. |
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| Address | Barcelona; Spain; June 2015 | ||||
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| Area | Expedition | Conference | IPCAI | ||
| Notes | IAM; MV; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ SBS2015b | Serial | 2613 | ||
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| Author | Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen | ||||
| Title | Quality Assessment of Optical Flow in Tagging MRI | Type | Conference Article | ||
| Year | 2015 | Publication | 5th Dutch Bio-Medical Engineering Conference BME2015 | Abbreviated Journal | |
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| Address | The Netherlands; January 2015 | ||||
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| Area | Expedition | Conference | BME | ||
| Notes | IAM; ADAS; 600.076; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ KMF2015 | Serial | 2616 | ||
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| Author | M. Cruz; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa | ||||
| Title | Cross-spectral image registration and fusion: an evaluation study | Type | Conference Article | ||
| Year | 2015 | Publication | 2nd International Conference on Machine Vision and Machine Learning | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | multispectral imaging; image registration; data fusion; infrared and visible spectra | ||||
| Abstract | This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different
spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented. |
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| Address | Barcelona; July 2015 | ||||
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| Area | Expedition | Conference | MVML | ||
| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ CAV2015 | Serial | 2629 | ||
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| Author | Jiaolong Xu | ||||
| Title | Domain Adaptation of Deformable Part-based Models | Type | Book Whole | ||
| Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | On-board pedestrian detection is crucial for Advanced Driver Assistance Systems
(ADAS). An accurate classi cation is fundamental for vision-based pedestrian detection. The underlying assumption for learning classi ers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classi ers. However, in practice, there are di erent reasons that can break this constancy assumption. Accordingly, reusing existing classi ers 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 thesis we focus on the domain adaptation of deformable part-based models (DPMs) for pedestrian detection. As a prof of concept, we use a computer graphic based synthetic dataset, i.e. a virtual world, as the source domain, and adapt the virtual-world trained DPM detector to various real-world dataset. We start by exploiting the maximum detection accuracy of the virtual-world trained DPM. Even though, when operating in various real-world datasets, the virtualworld trained detector still su er from accuracy degradation due to the domain gap of virtual and real worlds. We then focus on domain adaptation of DPM. At the rst step, we consider single source and single target domain adaptation and propose two batch learning methods, namely A-SSVM and SA-SSVM. Later, we further consider leveraging multiple target (sub-)domains for progressive domain adaptation and propose a hierarchical adaptive structured SVM (HA-SSVM) for optimization. Finally, we extend HA-SSVM for the challenging online domain adaptation problem, aiming at making the detector to automatically adapt to the target domain online, without any human intervention. All of the proposed methods in this thesis do not require revisiting source domain data. The evaluations are done on the Caltech pedestrian detection benchmark. Results show that SA-SSVM slightly outperforms A-SSVM and avoids accuracy drops as high as 15 points when comparing with a non-adapted detector. The hierarchical model learned by HA-SSVM further boosts the domain adaptation performance. Finally, the online domain adaptation method has demonstrated that it can achieve comparable accuracy to the batch learned models while not requiring manually label target domain examples. Domain adaptation for pedestrian detection is of paramount importance and a relatively unexplored area. We humbly hope the work in this thesis could provide foundations for future work in this area. |
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| Address | April 2015 | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Antonio Lopez | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-943427-1-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ Xu2015 | Serial | 2631 | ||
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| Author | Xavier Otazu; Olivier Penacchio; Xim Cerda-Company | ||||
| Title | An excitatory-inhibitory firing rate model accounts for brightness induction, colour induction and visual discomfort | Type | Conference Article | ||
| Year | 2015 | Publication | Barcelona Computational, Cognitive and Systems Neuroscience | Abbreviated Journal | |
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| Address | Barcelona; June 2015 | ||||
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| Area | Expedition | Conference | BARCCSYN | ||
| Notes | NEUROBIT;CIC | Approved | no | ||
| Call Number | Admin @ si @ OPC2015b | Serial | 2634 | ||
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| Author | Victor Campmany; Sergio Silva; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez | ||||
| Title | GPU-based pedestrian detection for autonomous driving | Type | Abstract | ||
| Year | 2015 | Publication | Programming and Tunning Massive Parallel Systems | Abbreviated Journal | PUMPS |
| Volume | Issue | Pages | |||
| Keywords | Autonomous Driving; ADAS; CUDA; Pedestrian Detection | ||||
| Abstract | Pedestrian detection for autonomous driving has gained a lot of prominence during the last few years. Besides the fact that it is one of the hardest tasks within computer vision, it involves huge computational costs. The real-time constraints in the field are tight, and regular processors are not able to handle the workload obtaining an acceptable ratio of frames per second (fps). Moreover, multiple cameras are required to obtain accurate results, so the need to speed up the process is even higher. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system. Further, we introduce significant algorithmic adjustments and optimizations to adapt the problem to the GPU architecture. The aim is to provide a system capable of running in real-time obtaining reliable results. | ||||
| Address | Barcelona; Spain | ||||
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| Series Editor | Series Title | Abbreviated Series Title | PUMPS | ||
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| Area | Expedition | Conference | PUMPS | ||
| Notes | ADAS; 600.076; 600.082; 600.085 | Approved | no | ||
| Call Number | ADAS @ adas @ CSM2015 | Serial | 2644 | ||
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| Author | Sergio Silva; Victor Campmany; Laura Sellart; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez | ||||
| Title | Autonomous GPU-based Driving | Type | Abstract | ||
| Year | 2015 | Publication | Programming and Tunning Massive Parallel Systems | Abbreviated Journal | PUMPS |
| Volume | Issue | Pages | |||
| Keywords | Autonomous Driving; ADAS; CUDA | ||||
| Abstract | Human factors cause most driving accidents; this is why nowadays is common to hear about autonomous driving as an alternative. Autonomous driving will not only increase safety, but also will develop a system of cooperative self-driving cars that will reduce pollution and congestion. Furthermore, it will provide more freedom to handicapped people, elderly or kids.
Autonomous Driving requires perceiving and understanding the vehicle environment (e.g., road, traffic signs, pedestrians, vehicles) using sensors (e.g., cameras, lidars, sonars, and radars), selflocalization (requiring GPS, inertial sensors and visual localization in precise maps), controlling the vehicle and planning the routes. These algorithms require high computation capability, and thanks to NVIDIA GPU acceleration this starts to become feasible. NVIDIA® is developing a new platform for boosting the Autonomous Driving capabilities that is able of managing the vehicle via CAN-Bus: the Drive™ PX. It has 8 ARM cores with dual accelerated Tegra® X1 chips. It has 12 synchronized camera inputs for 360º vehicle perception, 4G and Wi-Fi capabilities allowing vehicle communications and GPS and inertial sensors inputs for self-localization. Our research group has been selected for testing Drive™ PX. Accordingly, we are developing a Drive™ PX based autonomous car. Currently, we are porting our previous CPU based algorithms (e.g., Lane Departure Warning, Collision Warning, Automatic Cruise Control, Pedestrian Protection, or Semantic Segmentation) for running in the GPU. |
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| Address | Barcelona; Spain | ||||
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| Area | Expedition | Conference | PUMPS | ||
| Notes | ADAS; 600.076; 600.082; 600.085 | Approved | no | ||
| Call Number | ADAS @ adas @ SCS2015 | Serial | 2645 | ||
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| Author | Huamin Ren; Weifeng Liu; Soren Ingvor Olsen; Sergio Escalera; Thomas B. Moeslund | ||||
| Title | Unsupervised Behavior-Specific Dictionary Learning for Abnormal Event Detection | Type | Conference Article | ||
| Year | 2015 | Publication | 26th British Machine Vision Conference | Abbreviated Journal | |
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| Address | Swansea; uk; September 2015 | ||||
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| Area | Expedition | Conference | BMVC | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ RLO2015 | Serial | 2658 | ||
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| Author | Onur Ferhat; Arcadi Llanza; Fernando Vilariño | ||||
| Title | Gaze interaction for multi-display systems using natural light eye-tracker | Type | Conference Article | ||
| Year | 2015 | Publication | 2nd International Workshop on Solutions for Automatic Gaze Data Analysis | Abbreviated Journal | |
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| Address | Bielefeld; Germany; September 2015 | ||||
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| Area | Expedition | Conference | SAGA | ||
| Notes | MV;SIAI | Approved | no | ||
| Call Number | Admin @ si @ FLV2015b | Serial | 2676 | ||
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