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Author | Xim Cerda-Company; C. Alejandro Parraga; Xavier Otazu | ||||
Title | Which tone-mapping is the best? A comparative study of tone-mapping perceived quality | Type | Abstract | ||
Year | 2014 | Publication | Perception | Abbreviated Journal | |
Volume | 43 | Issue | Pages | 106 | |
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Abstract | Perception 43 ECVP Abstract Supplement
High-dynamic-range (HDR) imaging refers to the methods designed to increase the brightness dynamic range present in standard digital imaging techniques. This increase is achieved by taking the same picture under dierent exposure values and mapping the intensity levels into a single image by way of a tone-mapping operator (TMO). Currently, there is no agreement on how to evaluate the quality of dierent TMOs. In this work we psychophysically evaluate 15 dierent TMOs obtaining rankings based on the perceived properties of the resulting tone-mapped images. We performed two dierent experiments on a CRT calibrated display using 10 subjects: (1) a study of the internal relationships between grey-levels and (2) a pairwise comparison of the resulting 15 tone-mapped images. In (1) observers internally matched the grey-levels to a reference inside the tone-mapped images and in the real scene. In (2) observers performed a pairwise comparison of the tone-mapped images alongside the real scene. We obtained two rankings of the TMOs according their performance. In (1) the best algorithm was ICAM by J.Kuang et al (2007) and in (2) the best algorithm was a TMO by Krawczyk et al (2005). Our results also show no correlation between these two rankings. |
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Area | Expedition | Conference | ECVP | ||
Notes | NEUROBIT; 600.074 | Approved | no | ||
Call Number | Admin @ si @ CPO2014 | Serial | 2527 | ||
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Author | Xavier Otazu; Olivier Penacchio; Xim Cerda-Company | ||||
Title | Brightness and colour induction through contextual influences in V1 | Type | Conference Article | ||
Year | 2015 | Publication | Scottish Vision Group 2015 SGV2015 | Abbreviated Journal | |
Volume | 12 | Issue | 9 | Pages | 1208-2012 |
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Address | Carnoustie; Scotland; March 2015 | ||||
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Area | Expedition | Conference | SGV | ||
Notes | NEUROBIT; | Approved | no | ||
Call Number | Admin @ si @ OPC2015a | Serial | 2632 | ||
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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; | Approved | no | ||
Call Number | Admin @ si @ OPC2015b | Serial | 2634 | ||
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Author | Oscar Argudo; Marc Comino; Antonio Chica; Carlos Andujar; Felipe Lumbreras | ||||
Title | Segmentation of aerial images for plausible detail synthesis | Type | Journal Article | ||
Year | 2018 | Publication | Computers & Graphics | Abbreviated Journal | CG |
Volume | 71 | Issue | Pages | 23-34 | |
Keywords | Terrain editing; Detail synthesis; Vegetation synthesis; Terrain rendering; Image segmentation | ||||
Abstract | The visual enrichment of digital terrain models with plausible synthetic detail requires the segmentation of aerial images into a suitable collection of categories. In this paper we present a complete pipeline for segmenting high-resolution aerial images into a user-defined set of categories distinguishing e.g. terrain, sand, snow, water, and different types of vegetation. This segmentation-for-synthesis problem implies that per-pixel categories must be established according to the algorithms chosen for rendering the synthetic detail. This precludes the definition of a universal set of labels and hinders the construction of large training sets. Since artists might choose to add new categories on the fly, the whole pipeline must be robust against unbalanced datasets, and fast on both training and inference. Under these constraints, we analyze the contribution of common per-pixel descriptors, and compare the performance of state-of-the-art supervised learning algorithms. We report the findings of two user studies. The first one was conducted to analyze human accuracy when manually labeling aerial images. The second user study compares detailed terrains built using different segmentation strategies, including official land cover maps. These studies demonstrate that our approach can be used to turn digital elevation models into fully-featured, detailed terrains with minimal authoring efforts. | ||||
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ISSN | 0097-8493 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | MSIAU; 600.086; 600.118 | Approved | no | ||
Call Number | Admin @ si @ ACC2018 | Serial | 3147 | ||
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Author | Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris | ||||
Title | Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code | Type | Conference Article | ||
Year | 2015 | Publication | European Conference on Visual Perception ECVP2015 | Abbreviated Journal | |
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Address | Liverpool; uk; August 2015 | ||||
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Area | Expedition | Conference | ECVP | ||
Notes | NEUROBIT; | Approved | no | ||
Call Number | Admin @ si @ POW2015 | Serial | 2633 | ||
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Author | Maria Elena Meza-de-Luna; Juan Ramon Terven Salinas; Bogdan Raducanu; Joaquin Salas | ||||
Title | Assessing the Influence of Mirroring on the Perception of Professional Competence using Wearable Technology | Type | Journal Article | ||
Year | 2016 | Publication | IEEE Transactions on Affective Computing | Abbreviated Journal | TAC |
Volume | 9 | Issue | 2 | Pages | 161-175 |
Keywords | Mirroring; Nodding; Competence; Perception; Wearable Technology | ||||
Abstract | Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroring
events. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist’s nods is a better predictor than the number of customer’s nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras. |
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Notes | LAMP; 600.072; | Approved | no | ||
Call Number | Admin @ si @ MTR2016 | Serial | 2826 | ||
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Author | Manuel Graña; Bogdan Raducanu | ||||
Title | Special Issue on Bioinspired and knowledge based techniques and applications | Type | Journal Article | ||
Year | 2015 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
Volume | Issue | Pages | 1-3 | ||
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Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ GrR2015 | Serial | 2598 | ||
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Author | Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu | ||||
Title | New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired | Type | Journal Article | ||
Year | 2014 | Publication | Computer | Abbreviated Journal | COMP |
Volume | 47 | Issue | 4 | Pages | 52-58 |
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Abstract | Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices. | ||||
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ISSN | 0018-9162 | ISBN | Medium | ||
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Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ TSR2014a | Serial | 2317 | ||
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Author | Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu | ||||
Title | Robust Head Gestures Recognition for Assistive Technology | Type | Book Chapter | ||
Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | |
Volume | 8495 | Issue | Pages | 152-161 | |
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Abstract | This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture. | ||||
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Publisher | Springer International Publishing | Place of Publication | Editor | ||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | 0302-9743 | ISBN | 978-3-319-07490-0 | Medium | |
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Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ TSR2014b | Serial | 2505 | ||
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Author | Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas | ||||
Title | Head-gestures mirroring detection in dyadic social linteractions with computer vision-based wearable devices | Type | Journal Article | ||
Year | 2016 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
Volume | 175 | Issue | B | Pages | 866–876 |
Keywords | Head gestures recognition; Mirroring detection; Dyadic social interaction analysis; Wearable devices | ||||
Abstract | During face-to-face human interaction, nonverbal communication plays a fundamental role. A relevant aspect that takes part during social interactions is represented by mirroring, in which a person tends to mimic the non-verbal behavior (head and body gestures, vocal prosody, etc.) of the counterpart. In this paper, we introduce a computer vision-based system to detect mirroring in dyadic social interactions with the use of a wearable platform. In our context, mirroring is inferred as simultaneous head noddings displayed by the interlocutors. Our approach consists of the following steps: (1) facial features extraction; (2) facial features stabilization; (3) head nodding recognition; and (4) mirroring detection. Our system achieves a mirroring detection accuracy of 72% on a custom mirroring dataset. | ||||
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Notes | LAMP; 600.072; 600.068; | Approved | no | ||
Call Number | Admin @ si @ TRM2016 | Serial | 2721 | ||
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Author | Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas | ||||
Title | Evaluating Real-Time Mirroring of Head Gestures using Smart Glasses | Type | Conference Article | ||
Year | 2015 | Publication | 16th IEEE International Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 452-460 | ||
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Abstract | Mirroring occurs when one person tends to mimic the non-verbal communication of their counterparts. Even though mirroring is a complex phenomenon, in this study, we focus on the detection of head-nodding as a simple non-verbal communication cue due to its significance as a gesture displayed during social interactions. This paper introduces a computer vision-based method to detect mirroring through the analysis of head gestures using wearable cameras (smart glasses). In addition, we study how such a method can be used to explore perceived competence. The proposed method has been evaluated and the experiments demonstrate how static and wearable cameras seem to be equally effective to gather the information required for the analysis. | ||||
Address | Santiago de Chile; December 2015 | ||||
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Area | Expedition | Conference | ICCVW | ||
Notes | LAMP; 600.068; 600.072; | Approved | no | ||
Call Number | Admin @ si @ TRM2015 | Serial | 2722 | ||
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Author | Javad Zolfaghari Bengar; Joost Van de Weijer; Bartlomiej Twardowski; Bogdan Raducanu | ||||
Title | Reducing Label Effort: Self- Supervised Meets Active Learning | Type | Conference Article | ||
Year | 2021 | Publication | International Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 1631-1639 | ||
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Abstract | Active learning is a paradigm aimed at reducing the annotation effort by training the model on actively selected informative and/or representative samples. Another paradigm to reduce the annotation effort is self-training that learns from a large amount of unlabeled data in an unsupervised way and fine-tunes on few labeled samples. Recent developments in self-training have achieved very impressive results rivaling supervised learning on some datasets. The current work focuses on whether the two paradigms can benefit from each other. We studied object recognition datasets including CIFAR10, CIFAR100 and Tiny ImageNet with several labeling budgets for the evaluations. Our experiments reveal that self-training is remarkably more efficient than active learning at reducing the labeling effort, that for a low labeling budget, active learning offers no benefit to self-training, and finally that the combination of active learning and self-training is fruitful when the labeling budget is high. The performance gap between active learning trained either with self-training or from scratch diminishes as we approach to the point where almost half of the dataset is labeled. | ||||
Address | October 2021 | ||||
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Area | Expedition | Conference | ICCVW | ||
Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ ZVT2021 | Serial | 3672 | ||
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Author | Javad Zolfaghari Bengar; Bogdan Raducanu; Joost Van de Weijer | ||||
Title | When Deep Learners Change Their Mind: Learning Dynamics for Active Learning | Type | Conference Article | ||
Year | 2021 | Publication | 19th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
Volume | 13052 | Issue | 1 | Pages | 403-413 |
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Abstract | Active learning aims to select samples to be annotated that yield the largest performance improvement for the learning algorithm. Many methods approach this problem by measuring the informativeness of samples and do this based on the certainty of the network predictions for samples. However, it is well-known that neural networks are overly confident about their prediction and are therefore an untrustworthy source to assess sample informativeness. In this paper, we propose a new informativeness-based active learning method. Our measure is derived from the learning dynamics of a neural network. More precisely we track the label assignment of the unlabeled data pool during the training of the algorithm. We capture the learning dynamics with a metric called label-dispersion, which is low when the network consistently assigns the same label to the sample during the training of the network and high when the assigned label changes frequently. We show that label-dispersion is a promising predictor of the uncertainty of the network, and show on two benchmark datasets that an active learning algorithm based on label-dispersion obtains excellent results. | ||||
Address | September 2021 | ||||
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Area | Expedition | Conference | CAIP | ||
Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ ZRV2021 | Serial | 3673 | ||
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Author | Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Hugo Jair Escalante; Zhen Lei | ||||
Title | Surveillance Face Presentation Attack Detection Challenge | Type | Conference Article | ||
Year | 2023 | Publication | Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 6360-6370 | ||
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Abstract | Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, most of the studies lacked consideration of long-distance scenarios. Specifically, compared with FAS in traditional scenes such as phone unlocking, face payment, and self-service security inspection, FAS in long-distance such as station squares, parks, and self-service supermarkets are equally important, but it has not been sufficiently explored yet. In order to fill this gap in the FAS community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask). SuHiFiMask contains 10,195 videos from 101 subjects of different age groups, which are collected by 7 mainstream surveillance cameras. Based on this dataset and protocol-3 for evaluating the robustness of the algorithm under quality changes, we organized a face presentation attack detection challenge in surveillance scenarios. It attracted 180 teams for the development phase with a total of 37 teams qualifying for the final round. The organization team re-verified and re-ran the submitted code and used the results as the final ranking. In this paper, we present an overview of the challenge, including an introduction to the dataset used, the definition of the protocol, the evaluation metrics, and the announcement of the competition results. Finally, we present the top-ranked algorithms and the research ideas provided by the competition for attack detection in long-range surveillance scenarios. | ||||
Address | Vancouver; Canada; June 2023 | ||||
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Area | Expedition | Conference | CVPRW | ||
Notes | HuPBA | Approved | no | ||
Call Number | Admin @ si @ FLW2023 | Serial | 3917 | ||
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Author | Gemma Rotger; Francesc Moreno-Noguer; Felipe Lumbreras; Antonio Agudo | ||||
Title | Single view facial hair 3D reconstruction | Type | Conference Article | ||
Year | 2019 | Publication | 9th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 11867 | Issue | Pages | 423-436 | |
Keywords | 3D Vision; Shape Reconstruction; Facial Hair Modeling | ||||
Abstract | n this work, we introduce a novel energy-based framework that addresses the challenging problem of 3D reconstruction of facial hair from a single RGB image. To this end, we identify hair pixels over the image via texture analysis and then determine individual hair fibers that are modeled by means of a parametric hair model based on 3D helixes. We propose to minimize an energy composed of several terms, in order to adapt the hair parameters that better fit the image detections. The final hairs respond to the resulting fibers after a post-processing step where we encourage further realism. The resulting approach generates realistic facial hair fibers from solely an RGB image without assuming any training data nor user interaction. We provide an experimental evaluation on real-world pictures where several facial hair styles and image conditions are observed, showing consistent results and establishing a comparison with respect to competing approaches. | ||||
Address | Madrid; July 2019 | ||||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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Area | Expedition | Conference | IbPRIA | ||
Notes | MSIAU; 600.086; 600.130; 600.122 | Approved | no | ||
Call Number | Admin @ si @ | Serial | 3707 | ||
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