| |
Records |
Links |
|
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 |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Liverpool; uk; August 2015 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ECVP |
|
| |
Notes |
NEUROBIT; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ POW2015 |
Serial |
2633 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mohammad N. S. Jahromi; Pau Buch Cardona; Egils Avots; Kamal Nasrollahi; Sergio Escalera; Thomas B. Moeslund; Gholamreza Anbarjafari |
|
| |
Title |
Privacy-Constrained Biometric System for Non-cooperative Users |
Type |
Journal Article |
| |
Year |
2019 |
Publication |
Entropy |
Abbreviated Journal |
ENTROPY |
|
| |
Volume |
21 |
Issue |
11 |
Pages |
1033 |
|
| |
Keywords |
biometric recognition; multimodal-based human identification; privacy; deep learning |
|
| |
Abstract |
With the consolidation of the new data protection regulation paradigm for each individual within the European Union (EU), major biometric technologies are now confronted with many concerns related to user privacy in biometric deployments. When individual biometrics are disclosed, the sensitive information about his/her personal data such as financial or health are at high risk of being misused or compromised. This issue can be escalated considerably over scenarios of non-cooperative users, such as elderly people residing in care homes, with their inability to interact conveniently and securely with the biometric system. The primary goal of this study is to design a novel database to investigate the problem of automatic people recognition under privacy constraints. To do so, the collected data-set contains the subject’s hand and foot traits and excludes the face biometrics of individuals in order to protect their privacy. We carried out extensive simulations using different baseline methods, including deep learning. Simulation results show that, with the spatial features extracted from the subject sequence in both individual hand or foot videos, state-of-the-art deep models provide promising recognition performance. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
HuPBA; no proj |
Approved |
no |
|
| |
Call Number |
Admin @ si @ NBA2019 |
Serial |
3313 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh |
|
| |
Title |
Facial expression recognition based on multi observations with application to social robotics |
Type |
Book Chapter |
| |
Year |
2015 |
Publication |
Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
153-166 |
|
| |
Keywords |
|
|
| |
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 chapter, 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, viewand 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. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Nova Science publishers |
Place of Publication |
|
Editor |
Bruce Flores |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
LAMP; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DRB2015 |
Serial |
2720 |
|
| Permanent link to this record |
| |
|
| |
|
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. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0097-8493 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
MSIAU; 600.086; 600.118 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ACC2018 |
Serial |
3147 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0018-9162 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
LAMP; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ TSR2014a |
Serial |
2317 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona; June 2015 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
BARCCSYN |
|
| |
Notes |
NEUROBIT; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ OPC2015b |
Serial |
2634 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
| |
Notes |
MSIAU; 600.086; 600.130; 600.122 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3707 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika |
|
| |
Title |
Multi-observation Face Recognition in Videos based on Label Propagation |
Type |
Conference Article |
| |
Year |
2015 |
Publication |
6th Workshop on Analysis and Modeling of Faces and Gestures AMFG2015 |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
10-17 |
|
| |
Keywords |
|
|
| |
Abstract |
In order to deal with the huge amount of content generated by social media, especially for indexing and retrieval purposes, the focus shifted from single object recognition to multi-observation object recognition. Of particular interest is the problem of face recognition (used as primary cue for persons’ identity assessment), since it is highly required by popular social media search engines like Facebook and Youtube. Recently, several approaches for graph-based label propagation were proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot cope properly with the rapid and frequent changes in data appearance, a phenomenon intrinsically related with video sequences. In this paper, we
propose a novel approach for efficient and adaptive graph construction, based on a two-phase scheme: (i) the first phase is used to adaptively find the neighbors of a sample and also to find the adequate weights for the minimization function of the second phase; (ii) in the second phase, the
selected neighbors along with their corresponding weights are used to locally and collaboratively estimate the sparse affinity matrix weights. Experimental results performed on Honda Video Database (HVDB) and a subset of video
sequences extracted from the popular TV-series ’Friends’ show a distinct advantage of the proposed method over the existing standard graph construction methods. |
|
| |
Address |
Boston; USA; June 2015 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CVPRW |
|
| |
Notes |
LAMP; 600.068; 600.072; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RBD2015 |
Serial |
2627 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Cristina Palmero; Javier Selva; Mohammad Ali Bagheri; Sergio Escalera |
|
| |
Title |
Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues |
Type |
Conference Article |
| |
Year |
2018 |
Publication |
29th British Machine Vision Conference |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Gaze behavior is an important non-verbal cue in social signal processing and humancomputer interaction. In this paper, we tackle the problem of person- and head poseindependent 3D gaze estimation from remote cameras, using a multi-modal recurrent convolutional neural network (CNN). We propose to combine face, eyes region, and face landmarks as individual streams in a CNN to estimate gaze in still images. Then, we exploit the dynamic nature of gaze by feeding the learned features of all the frames in a sequence to a many-to-one recurrent module that predicts the 3D gaze vector of the last frame. Our multi-modal static solution is evaluated on a wide range of head poses and gaze directions, achieving a significant improvement of 14.6% over the state of the art on
EYEDIAP dataset, further improved by 4% when the temporal modality is included. |
|
| |
Address |
Newcastle; UK; September 2018 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
BMVC |
|
| |
Notes |
HUPBA; no proj |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PSB2018 |
Serial |
3208 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Gemma Rotger; Felipe Lumbreras; Francesc Moreno-Noguer; Antonio Agudo |
|
| |
Title |
2D-to-3D Facial Expression Transfer |
Type |
Conference Article |
| |
Year |
2018 |
Publication |
24th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
2008 - 2013 |
|
| |
Keywords |
|
|
| |
Abstract |
Automatically changing the expression and physical features of a face from an input image is a topic that has been traditionally tackled in a 2D domain. In this paper, we bring this problem to 3D and propose a framework that given an
input RGB video of a human face under a neutral expression, initially computes his/her 3D shape and then performs a transfer to a new and potentially non-observed expression. For this purpose, we parameterize the rest shape –obtained from standard factorization approaches over the input video– using a triangular
mesh which is further clustered into larger macro-segments. The expression transfer problem is then posed as a direct mapping between this shape and a source shape, such as the blend shapes of an off-the-shelf 3D dataset of human facial expressions. The mapping is resolved to be geometrically consistent between 3D models by requiring points in specific regions to map on semantic
equivalent regions. We validate the approach on several synthetic and real examples of input faces that largely differ from the source shapes, yielding very realistic expression transfers even in cases with topology changes, such as a synthetic video sequence of a single-eyed cyclops. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
MSIAU; 600.086; 600.130; 600.118 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RLM2018 |
Serial |
3232 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Singapore; November 2014 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ACCV |
|
| |
Notes |
LAMP; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RBD2014 |
Serial |
2599 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
| |
Keywords |
|
|
| |
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 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CAIP |
|
| |
Notes |
LAMP; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ZRV2021 |
Serial |
3673 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
| |
Keywords |
|
|
| |
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 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICCVW |
|
| |
Notes |
LAMP; 600.068; 600.072; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ TRM2015 |
Serial |
2722 |
|
| Permanent link to this record |
