|   | 
Details
   web
Records
Author Sounak Dey; Pau Riba; Anjan Dutta; Josep Llados; Yi-Zhe Song
Title Doodle to Search: Practical Zero-Shot Sketch-Based Image Retrieval Type Conference Article
Year 2019 Publication IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 2179-2188
Keywords
Abstract In this paper, we investigate the problem of zero-shot sketch-based image retrieval (ZS-SBIR), where human sketches are used as queries to conduct retrieval of photos from unseen categories. We importantly advance prior arts by proposing a novel ZS-SBIR scenario that represents a firm step forward in its practical application. The new setting uniquely recognizes two important yet often neglected challenges of practical ZS-SBIR, (i) the large domain gap between amateur sketch and photo, and (ii) the necessity for moving towards large-scale retrieval. We first contribute to the community a novel ZS-SBIR dataset, QuickDraw-Extended, that consists of 330,000 sketches and 204,000 photos spanning across 110 categories. Highly abstract amateur human sketches are purposefully sourced to maximize the domain gap, instead of ones included in existing datasets that can often be semi-photorealistic. We then formulate a ZS-SBIR framework to jointly model sketches and photos into a common embedding space. A novel strategy to mine the mutual information among domains is specifically engineered to alleviate the domain gap. External semantic knowledge is further embedded to aid semantic transfer. We show that, rather surprisingly, retrieval performance significantly outperforms that of state-of-the-art on existing datasets that can already be achieved using a reduced version of our model. We further demonstrate the superior performance of our full model by comparing with a number of alternatives on the newly proposed dataset. The new dataset, plus all training and testing code of our model, will be publicly released to facilitate future research.
Address Long beach; CA; USA; June 2019
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 CVPR
Notes DAG; 600.140; 600.121; 600.097 Approved no
Call Number (down) Admin @ si @ DRD2019 Serial 3462
Permanent link to this record
 

 
Author Alexey Dosovitskiy; German Ros; Felipe Codevilla; Antonio Lopez; Vladlen Koltun
Title CARLA: An Open Urban Driving Simulator Type Conference Article
Year 2017 Publication 1st Annual Conference on Robot Learning. Proceedings of Machine Learning Abbreviated Journal
Volume 78 Issue Pages 1-16
Keywords Autonomous driving; sensorimotor control; simulation
Abstract We introduce CARLA, an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous urban driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites and environmental conditions. We use CARLA to study the performance of three approaches to autonomous driving: a classic modular pipeline, an endto-end
model trained via imitation learning, and an end-to-end model trained via
reinforcement learning. The approaches are evaluated in controlled scenarios of
increasing difficulty, and their performance is examined via metrics provided by CARLA, illustrating the platform’s utility for autonomous driving research.
Address Mountain View; CA; USA; November 2017
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 CORL
Notes ADAS; 600.085; 600.118 Approved no
Call Number (down) Admin @ si @ DRC2017 Serial 2988
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 OR;MV Approved no
Call Number (down) Admin @ si @ DRB2015 Serial 2720
Permanent link to this record
 

 
Author Anjan Dutta; Umapada Pal; Josep Llados
Title Compact Correlated Features for Writer Independent Signature Verification Type Conference Article
Year 2016 Publication 23rd International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper considers the offline signature verification problem which is considered to be an important research line in the field of pattern recognition. In this work we propose hybrid features that consider the local features and their global statistics in the signature image. This has been done by creating a vocabulary of histogram of oriented gradients (HOGs). We impose weights on these local features based on the height information of water reservoirs obtained from the signature. Spatial information between local features are thought to play a vital role in considering the geometry of the signatures which distinguishes the originals from the forged ones. Nevertheless, learning a condensed set of higher order neighbouring features based on visual words, e.g., doublets and triplets, continues to be a challenging problem as possible combinations of visual words grow exponentially. To avoid this explosion of size, we create a code of local pairwise features which are represented as joint descriptors. Local features are paired based on the edges of a graph representation built upon the Delaunay triangulation. We reveal the advantage of combining both type of visual codebooks (order one and pairwise) for signature verification task. This is validated through an encouraging result on two benchmark datasets viz. CEDAR and GPDS300.
Address Cancun; Mexico; December 2016
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 DAG; 600.097 Approved no
Call Number (down) Admin @ si @ DPL2016 Serial 2875
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu
Title Out-of-Sample Embedding for Manifold Learning Applied to Face Recognition Type Conference Article
Year 2013 Publication IEEE International Workshop on Analysis and Modeling of Faces and Gestures Abbreviated Journal
Volume Issue Pages 862-868
Keywords
Abstract Manifold learning techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data---the out-of-sample problem. For the first aspect, the proposed schemes were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only reached for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that sparse coding theory not only serves for automatic graph reconstruction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the k-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on four public face databases. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes.
Address Portland; USA; June 2013
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 OR; 600.046;MV Approved no
Call Number (down) Admin @ si @ DoR2013 Serial 2236
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu
Title Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation Type Book Chapter
Year 2012 Publication Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions Abbreviated Journal
Volume Issue Pages 157-178
Keywords
Abstract
Address
Corporate Author Thesis
Publisher NOVA Publishers Place of Publication Editor S.E. Carter
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number (down) Admin @ si @ DoR2012 Serial 2183
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu
Title Subtle Facial Expression Recognition in Still Images and Videos Type Book Chapter
Year 2011 Publication Advances in Face Image Analysis: Techniques and Technologies Abbreviated Journal
Volume Issue 14 Pages 259-277
Keywords
Abstract This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM).
Address
Corporate Author Thesis
Publisher IGI-Global Place of Publication New York, USA Editor Yu-Jin Zhang
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-6152-0991-0 Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number (down) Admin @ si @ DoR2011 Serial 1751
Permanent link to this record
 

 
Author Fadi Dornaika; Franck Davoine
Title On appearance based face and facial action tracking Type Journal
Year 2006 Publication IEEE Transactions on Circuits and Systems for Video Technology, 16(9): 1838–1853 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 Approved no
Call Number (down) Admin @ si @ DoD2006b Serial 732
Permanent link to this record
 

 
Author Fadi Dornaika; Franck Davoine
Title Facial expression recognition using auto-regressive models Type Miscellaneous
Year 2006 Publication 18th International Conference on Pattern Recognition (ICPR´06), ISBN: 0–7695–2521–0, 4: 520–523 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Hong Kong
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 Approved no
Call Number (down) Admin @ si @ DoD2006a Serial 734
Permanent link to this record
 

 
Author Fadi Dornaika; Franck Davoine
Title Simultaneous Facial Action Tracking and Expression Recognition using a Particle Filter Type Miscellaneous
Year 2005 Publication 10th IEEE Int. Conference on Computer Vision (ICCV) Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Beijing (China)
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 Approved no
Call Number (down) Admin @ si @ DoD2005d Serial 581
Permanent link to this record
 

 
Author Fadi Dornaika; Franck Davoine
Title SFM for planar scenes using image derivatives Type Miscellaneous
Year 2005 Publication IEEE Int. Conference on Image Processing, 1088–1091 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Genova (Italy)
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 Approved no
Call Number (down) Admin @ si @ DoD2005b Serial 598
Permanent link to this record
 

 
Author Fadi Dornaika; Franck Davoine
Title Facial expression recognition in continuous videos using dynamic programming Type Miscellaneous
Year 2005 Publication IEEE Int. Conference on Image Processing Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Genova (Italy)
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 Approved no
Call Number (down) Admin @ si @ DoD2005a Serial 597
Permanent link to this record
 

 
Author Fadi Dornaika; J. Ahlberg
Title Fitting 3D face models for tracking and active appearance model training Type Journal
Year 2006 Publication Image and Vision Computing, 24(9): 1010–1024 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 Approved no
Call Number (down) Admin @ si @ DoA2006 Serial 733
Permanent link to this record
 

 
Author Sounak Dey; Anguelos Nicolaou; Josep Llados; Umapada Pal
Title Evaluation of the Effect of Improper Segmentation on Word Spotting Type Journal Article
Year 2019 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 22 Issue Pages 361-374
Keywords
Abstract Word spotting is an important recognition task in large-scale retrieval of document collections. In most of the cases, methods are developed and evaluated assuming perfect word segmentation. In this paper, we propose an experimental framework to quantify the goodness that word segmentation has on the performance achieved by word spotting methods in identical unbiased conditions. The framework consists of generating systematic distortions on segmentation and retrieving the original queries from the distorted dataset. We have tested our framework on several established and state-of-the-art methods using George Washington and Barcelona Marriage Datasets. The experiments done allow for an estimate of the end-to-end performance of word spotting methods.
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 DAG; 600.097; 600.084; 600.121; 600.140; 600.129 Approved no
Call Number (down) Admin @ si @ DNL2019 Serial 3455
Permanent link to this record
 

 
Author Sounak Dey; Anguelos Nicolaou; Josep Llados; Umapada Pal
Title Local Binary Pattern for Word Spotting in Handwritten Historical Document Type Conference Article
Year 2016 Publication Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) Abbreviated Journal
Volume Issue Pages 574-583
Keywords Local binary patterns; Spatial sampling; Learning-free; Word spotting; Handwritten; Historical document analysis; Large-scale data
Abstract Digital libraries store images which can be highly degraded and to index this kind of images we resort to word spotting as our information retrieval system. Information retrieval for handwritten document images is more challenging due to the difficulties in complex layout analysis, large variations of writing styles, and degradation or low quality of historical manuscripts. This paper presents a simple innovative learning-free method for word spotting from large scale historical documents combining Local Binary Pattern (LBP) and spatial sampling. This method offers three advantages: firstly, it operates in completely learning free paradigm which is very different from unsupervised learning methods, secondly, the computational time is significantly low because of the LBP features, which are very fast to compute, and thirdly, the method can be used in scenarios where annotations are not available. Finally, we compare the results of our proposed retrieval method with other methods in the literature and we obtain the best results in the learning free paradigm.
Address Merida; Mexico; December 2016
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 S+SSPR
Notes DAG; 600.097; 602.006; 603.053 Approved no
Call Number (down) Admin @ si @ DNL2016 Serial 2876
Permanent link to this record