| Records |
| Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
| Title |
Rendering ground truth data sets to detect shadows cast by static objects in outdoors |
Type |
Journal Article |
| Year |
2014 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
| Volume |
70 |
Issue |
1 |
Pages |
557-571 |
| Keywords |
Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection |
| Abstract |
In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically. |
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Springer US |
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Edition |
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| ISSN |
1380-7501 |
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| Notes |
OR;MV |
Approved |
no |
Call Number  |
Admin @ si @ ISR2014 |
Serial |
2229 |
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| Author |
Firat Ismailoglu; Ida G. Sprinkhuizen-Kuyper; Evgueni Smirnov; Sergio Escalera; Ralf Peeters |
| Title |
Fractional Programming Weighted Decoding for Error-Correcting Output Codes |
Type |
Conference Article |
| Year |
2015 |
Publication |
Multiple Classifier Systems, Proceedings of 12th International Workshop , MCS 2015 |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
38-50 |
| Keywords |
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| Abstract |
In order to increase the classification performance obtained using Error-Correcting Output Codes designs (ECOC), introducing weights in the decoding phase of the ECOC has attracted a lot of interest. In this work, we present a method for ECOC designs that focuses on increasing hypothesis margin on the data samples given a base classifier. While achieving this, we implicitly reward the base classifiers with high performance, whereas punish those with low performance. The resulting objective function is of the fractional programming type and we deal with this problem through the Dinkelbach’s Algorithm. The conducted tests over well known UCI datasets show that the presented method is superior to the unweighted decoding and that it outperforms the results of the state-of-the-art weighted decoding methods in most of the performed experiments. |
| Address |
Gunzburg; Germany; June 2015 |
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| Publisher |
Springer International Publishing |
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ISBN |
978-3-319-20247-1 |
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Conference |
MCS |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ ISS2015 |
Serial |
2601 |
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| Author |
Mohammad N. S. Jahromi; Morten Bojesen Bonderup; Maryam Asadi-Aghbolaghi; Egils Avots; Kamal Nasrollahi; Sergio Escalera; Shohreh Kasaei; Thomas B. Moeslund; Gholamreza Anbarjafari |
| Title |
Automatic Access Control Based on Face and Hand Biometrics in a Non-cooperative Context |
Type |
Conference Article |
| Year |
2018 |
Publication |
IEEE Winter Applications of Computer Vision Workshops |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
28-36 |
| Keywords |
IEEE Winter Applications of Computer Vision Workshops |
| Abstract |
Automatic access control systems (ACS) based on the human biometrics or physical tokens are widely employed in public and private areas. Yet these systems, in their conventional forms, are restricted to active interaction from the users. In scenarios where users are not cooperating with the system, these systems are challenged. Failure in cooperation with the biometric systems might be intentional or because the users are incapable of handling the interaction procedure with the biometric system or simply forget to cooperate with it, due to for example, illness like dementia. This work introduces a challenging bimodal database, including face and hand information of the users when they approach a door to open it by its handle in a noncooperative context. We have defined two (an easy and a challenging) protocols on how to use the database. We have reported results on many baseline methods, including deep learning techniques as well as conventional methods on the database. The obtained results show the merit of the proposed database and the challenging nature of access control with non-cooperative users. |
| Address |
Lake Tahoe; USA; March 2018 |
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Conference |
WACVW |
| Notes |
HUPBA; 602.133 |
Approved |
no |
| Call Number |
Admin @ si @ JBA2018 |
Serial |
3121 |
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| Author |
Julio C. S. Jacques Junior; Xavier Baro; Sergio Escalera |
| Title |
Exploiting feature representations through similarity learning and ranking aggregation for person re-identification |
Type |
Conference Article |
| Year |
2017 |
Publication |
12th IEEE International Conference on Automatic Face and Gesture Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
Person re-identification has received special attentionby the human analysis community in the last few years.To address the challenges in this field, many researchers haveproposed different strategies, which basically exploit eithercross-view invariant features or cross-view robust metrics. Inthis work we propose to combine different feature representationsthrough ranking aggregation. Spatial information, whichpotentially benefits the person matching, is represented usinga 2D body model, from which color and texture informationare extracted and combined. We also consider contextualinformation (background and foreground data), automaticallyextracted via Deep Decompositional Network, and the usage ofConvolutional Neural Network (CNN) features. To describe thematching between images we use the polynomial feature map,also taking into account local and global information. Finally,the Stuart ranking aggregation method is employed to combinecomplementary ranking lists obtained from different featurerepresentations. Experimental results demonstrated that weimprove the state-of-the-art on VIPeR and PRID450s datasets,achieving 58.77% and 71.56% on top-1 rank recognitionrate, respectively, as well as obtaining competitive results onCUHK01 dataset. |
| Address |
Washington; DC; USA; May 2017 |
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FG |
| Notes |
HUPBA; 602.143 |
Approved |
no |
| Call Number |
Admin @ si @ JBE2017 |
Serial |
2923 |
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| Author |
Julio C. S. Jacques Junior; Xavier Baro; Sergio Escalera |
| Title |
Exploiting feature representations through similarity learning, post-ranking and ranking aggregation for person re-identification |
Type |
Journal Article |
| Year |
2018 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
| Volume |
79 |
Issue |
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Pages |
76-85 |
| Keywords |
|
| Abstract |
Person re-identification has received special attention by the human analysis community in the last few years. To address the challenges in this field, many researchers have proposed different strategies, which basically exploit either cross-view invariant features or cross-view robust metrics. In this work, we propose to exploit a post-ranking approach and combine different feature representations through ranking aggregation. Spatial information, which potentially benefits the person matching, is represented using a 2D body model, from which color and texture information are extracted and combined. We also consider background/foreground information, automatically extracted via Deep Decompositional Network, and the usage of Convolutional Neural Network (CNN) features. To describe the matching between images we use the polynomial feature map, also taking into account local and global information. The Discriminant Context Information Analysis based post-ranking approach is used to improve initial ranking lists. Finally, the Stuart ranking aggregation method is employed to combine complementary ranking lists obtained from different feature representations. Experimental results demonstrated that we improve the state-of-the-art on VIPeR and PRID450s datasets, achieving 67.21% and 75.64% on top-1 rank recognition rate, respectively, as well as obtaining competitive results on CUHK01 dataset. |
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| Notes |
HuPBA; 602.143 |
Approved |
no |
| Call Number |
Admin @ si @ JBE2018 |
Serial |
3138 |
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| Author |
Domicele Jonauskaite; Lucia Camenzind; C. Alejandro Parraga; Cecile N Diouf; Mathieu Mercapide Ducommun; Lauriane Müller; Melanie Norberg; Christine Mohr |
| Title |
Colour-emotion associations in individuals with red-green colour blindness |
Type |
Journal Article |
| Year |
2021 |
Publication |
PeerJ |
Abbreviated Journal |
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| Volume |
9 |
Issue |
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Pages |
e11180 |
| Keywords |
Affect; Chromotherapy; Colour cognition; Colour vision deficiency; Cross-modal correspondences; Daltonism; Deuteranopia; Dichromatic; Emotion; Protanopia. |
| Abstract |
Colours and emotions are associated in languages and traditions. Some of us may convey sadness by saying feeling blue or by wearing black clothes at funerals. The first example is a conceptual experience of colour and the second example is an immediate perceptual experience of colour. To investigate whether one or the other type of experience more strongly drives colour-emotion associations, we tested 64 congenitally red-green colour-blind men and 66 non-colour-blind men. All participants associated 12 colours, presented as terms or patches, with 20 emotion concepts, and rated intensities of the associated emotions. We found that colour-blind and non-colour-blind men associated similar emotions with colours, irrespective of whether colours were conveyed via terms (r = .82) or patches (r = .80). The colour-emotion associations and the emotion intensities were not modulated by participants' severity of colour blindness. Hinting at some additional, although minor, role of actual colour perception, the consistencies in associations for colour terms and patches were higher in non-colour-blind than colour-blind men. Together, these results suggest that colour-emotion associations in adults do not require immediate perceptual colour experiences, as conceptual experiences are sufficient. |
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| Notes |
CIC; LAMP; 600.120; 600.128 |
Approved |
no |
| Call Number |
Admin @ si @ JCP2021 |
Serial |
3564 |
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| Author |
Zhong Jin; Franck Davoine; Zhen Lou |
| Title |
Facial expression analysis by using KPCA |
Type |
Miscellaneous |
| Year |
2003 |
Publication |
IEEE International Conference on Robotics, Intelligent Systems and Signal Processing (IEEE RISSP 2003), pp736–741 |
Abbreviated Journal |
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| Address |
Changsha, Hunan, China |
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no |
| Call Number |
Admin @ si @ JDL2003 |
Serial |
431 |
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| Author |
Zhong Jin; Franck Davoine; Zhen Lou |
| Title |
An Effective EM Algorithm for PCA Mixture Model |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
Structural and Statistical Pattern Recognition, Lecture Notes in Computer Science, 3138:626–634 |
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| Address |
Lisbon, Portugal |
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no |
| Call Number |
Admin @ si @ JDL2004 |
Serial |
482 |
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| Author |
Zhong Jin; Franck Davoine; Zhen Lou; Jing-Yu Yang |
| Title |
A novel PCA-based Bayes classifier and face analysis |
Type |
Book Chapter |
| Year |
2006 |
Publication |
International Conference on Advances in Biometrics (ICB’06), LNCS 3832: 144–150 |
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| Address |
Hong Kong |
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no |
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Admin @ si @ JDL2006 |
Serial |
624 |
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| Author |
Jean-Pascal Jacob; Mariella Dimiccoli; Lionel Moisan |
| Title |
Active skeleton for bacteria modeling |
Type |
Journal Article |
| Year |
2016 |
Publication |
Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization |
Abbreviated Journal |
CMBBE |
| Volume |
5 |
Issue |
4 |
Pages |
274-286 |
| Keywords |
Bacteria modelling; medial axis; active contours; active skeleton; shape contraints |
| Abstract |
The investigation of spatio-temporal dynamics of bacterial cells and their molecular components requires automated image analysis tools to track cell shape properties and molecular component locations inside the cells. In the study of bacteria aging, the molecular components of interest are protein aggregates accumulated near bacteria boundaries. This particular location makes very ambiguous the correspondence between aggregates and cells, since computing accurately bacteria boundaries in phase-contrast time-lapse imaging is a challenging task. This paper proposes an active skeleton formulation for bacteria modeling which provides several advantages: an easy computation of shape properties (perimeter, length, thickness, orientation), an improved boundary accuracy in noisy images, and a natural bacteria-centered coordinate system that permits the intrinsic location of molecular components inside the cell. Starting from an initial skeleton estimate, the medial axis of the bacterium is obtained by minimizing an energy function which incorporates bacteria shape constraints. Experimental results on biological images and comparative evaluation of the performances validate the proposed approach for modeling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the proposed method can be found online at this http URL |
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MILAB |
Approved |
no |
| Call Number |
Admin @ si @ JDM2016 |
Serial |
2711 |
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| Author |
Domicele Jonauskaite; Nele Dael; C. Alejandro Parraga; Laetitia Chevre; Alejandro Garcia Sanchez; Christine Mohr |
| Title |
Stripping #The Dress: The importance of contextual information on inter-individual differences in colour perception |
Type |
Journal Article |
| Year |
2018 |
Publication |
Psychological Research |
Abbreviated Journal |
PSYCHO R |
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Issue |
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Pages |
1-15 |
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| Abstract |
In 2015, a picture of a Dress (henceforth the Dress) triggered popular and scientific interest; some reported seeing the Dress in white and gold (W&G) and others in blue and black (B&B). We aimed to describe the phenomenon and investigate the role of contextualization. Few days after the Dress had appeared on the Internet, we projected it to 240 students on two large screens in the classroom. Participants reported seeing the Dress in B&B (48%), W&G (38%), or blue and brown (B&Br; 7%). Amongst numerous socio-demographic variables, we only observed that W&G viewers were most likely to have always seen the Dress as W&G. In the laboratory, we tested how much contextual information is necessary for the phenomenon to occur. Fifty-seven participants selected colours most precisely matching predominant colours of parts or the full Dress. We presented, in this order, small squares (a), vertical strips (b), and the full Dress (c). We found that (1) B&B, B&Br, and W&G viewers had selected colours differing in lightness and chroma levels for contextualized images only (b, c conditions) and hue for fully contextualized condition only (c) and (2) B&B viewers selected colours most closely matching displayed colours of the Dress. Thus, the Dress phenomenon emerges due to inter-individual differences in subjectively perceived lightness, chroma, and hue, at least when all aspects of the picture need to be integrated. Our results support the previous conclusions that contextual information is key to colour perception; it should be important to understand how this actually happens. |
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| Notes |
NEUROBIT; no proj |
Approved |
no |
| Call Number |
Admin @ si @ JDP2018 |
Serial |
3149 |
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| Author |
Julio C. S. Jacques Junior; Yagmur Gucluturk; Marc Perez; Umut Guçlu; Carlos Andujar; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon; Marcel A. J. van Gerven; Rob van Lier; Sergio Escalera |
| Title |
First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis |
Type |
Journal Article |
| Year |
2022 |
Publication |
IEEE Transactions on Affective Computing |
Abbreviated Journal |
TAC |
| Volume |
13 |
Issue |
1 |
Pages |
75-95 |
| Keywords |
Personality computing; first impressions; person perception; big-five; subjective bias; computer vision; machine learning; nonverbal signals; facial expression; gesture; speech analysis; multi-modal recognition |
| Abstract |
Personality analysis has been widely studied in psychology, neuropsychology, and signal processing fields, among others. From the past few years, it also became an attractive research area in visual computing. From the computational point of view, by far speech and text have been the most considered cues of information for analyzing personality. However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data. Recent computer vision approaches are able to accurately analyze human faces, body postures and behaviors, and use these information to infer apparent personality traits. Because of the overwhelming research interest in this topic, and of the potential impact that this sort of methods could have in society, we present in this paper an up-to-date review of existing vision-based approaches for apparent personality trait recognition. We describe seminal and cutting edge works on the subject, discussing and comparing their distinctive features and limitations. Future venues of research in the field are identified and discussed. Furthermore, aspects on the subjectivity in data labeling/evaluation, as well as current datasets and challenges organized to push the research on the field are reviewed. |
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1 Jan.-March 2022 |
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HuPBA |
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no |
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Admin @ si @ JGP2022 |
Serial |
3724 |
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| Author |
Zhong Jin; Franck Davoine |
| Title |
Orthogonal ICA Representation Of Images |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
8th International Conference on Control, Automation, Robotics and Vision, 369–374 |
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Kunming (China) |
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no |
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Admin @ si @ JiD2004 |
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499 |
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Hugo Jair Escalante; Heysem Kaya; Albert Ali Salah; Sergio Escalera; Yagmur Gucluturk; Umut Guclu; Xavier Baro; Isabelle Guyon; Julio C. S. Jacques Junior; Meysam Madadi; Stephane Ayache; Evelyne Viegas; Furkan Gurpinar; Achmadnoer Sukma Wicaksana; Cynthia C. S. Liem; Marcel A. J. van Gerven; Rob van Lier |
| Title |
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos |
Type |
Miscellaneous |
| Year |
2018 |
Publication |
Arxiv |
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Issue |
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Pages |
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| Abstract |
Explainability and interpretability are two critical aspects of decision support systems. Within computer vision, they are critical in certain tasks related to human behavior analysis such as in health care applications. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of computer vision with an emphasis on looking at people tasks. Specifically, we review and study those mechanisms in the context of first impressions analysis. To the best of our knowledge, this is the first effort in this direction. Additionally, we describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, the evaluation protocol, and summarize the results of the challenge. Finally, derived from our study, we outline research opportunities that we foresee will be decisive in the near future for the development of the explainable computer vision field. |
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HUPBA |
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no |
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Admin @ si @ JKS2018 |
Serial |
3095 |
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Raquel Justo; Leila Ben Letaifa; Cristina Palmero; Eduardo Gonzalez-Fraile; Anna Torp Johansen; Alain Vazquez; Gennaro Cordasco; Stephan Schlogl; Begoña Fernandez-Ruanova; Micaela Silva; Sergio Escalera; Mikel de Velasco; Joffre Tenorio-Laranga; Anna Esposito; Maria Korsnes; M. Ines Torres |
| Title |
Analysis of the Interaction between Elderly People and a Simulated Virtual Coach, Journal of Ambient Intelligence and Humanized Computing |
Type |
Journal Article |
| Year |
2020 |
Publication |
Journal of Ambient Intelligence and Humanized Computing |
Abbreviated Journal |
AIHC |
| Volume |
11 |
Issue |
12 |
Pages |
6125-6140 |
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| Abstract |
The EMPATHIC project develops and validates new interaction paradigms for personalized virtual coaches (VC) to promote healthy and independent aging. To this end, the work presented in this paper is aimed to analyze the interaction between the EMPATHIC-VC and the users. One of the goals of the project is to ensure an end-user driven design, involving senior users from the beginning and during each phase of the project. Thus, the paper focuses on some sessions where the seniors carried out interactions with a Wizard of Oz driven, simulated system. A coaching strategy based on the GROW model was used throughout these sessions so as to guide interactions and engage the elderly with the goals of the project. In this interaction framework, both the human and the system behavior were analyzed. The way the wizard implements the GROW coaching strategy is a key aspect of the system behavior during the interaction. The language used by the virtual agent as well as his or her physical aspect are also important cues that were analyzed. Regarding the user behavior, the vocal communication provides information about the speaker’s emotional status, that is closely related to human behavior and which can be extracted from the speech and language analysis. In the same way, the analysis of the facial expression, gazes and gestures can provide information on the non verbal human communication even when the user is not talking. In addition, in order to engage senior users, their preferences and likes had to be considered. To this end, the effect of the VC on the users was gathered by means of direct questionnaires. These analyses have shown a positive and calm behavior of users when interacting with the simulated virtual coach as well as some difficulties of the system to develop the proposed coaching strategy. |
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HuPBA; no proj |
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no |
| Call Number |
Admin @ si @ JLP2020 |
Serial |
3443 |
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