| Home | [211–220] << 221 222 223 224 225 226 227 228 >> |
|
| Records | |||||
|---|---|---|---|---|---|
| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach | Type | Conference Article | ||
| Year | 2009 | Publication | IEEE Workshop on Applications of Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | |||||
| Abstract | This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach. | ||||
| Address | Utah, USA | ||||
| 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 | 1550-5790 | ISBN | 978-1-4244-5497-6 | Medium | |
| Area | Expedition | Conference | WACV | ||
Notes  |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DoR2009b | Serial | 1256 | ||
| Permanent link to this record | |||||
| Author | Bogdan Raducanu; Fadi Dornaika | ||||
| Title | Natural Facial Expression Recognition Using Dynamic and Static Schemes | Type | Conference Article | ||
| Year | 2009 | Publication | 5th International Symposium on Visual Computing | Abbreviated Journal | |
| Volume | 5875 | Issue | Pages | 730–739 | |
| Keywords | |||||
| Abstract | Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences. | ||||
| Address | Las Vegas, USA | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-10330-8 | Medium | |
| Area | Expedition | Conference | ISVC | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RaD2009 | Serial | 1257 | ||
| Permanent link to this record | |||||
| Author | Agata Lapedriza | ||||
| Title | Multitask Learning Techniques for Automatic Face Classification | Type | Book Whole | ||
| Year | 2009 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | |||||
| Abstract | Automatic face classification is currently a popular research area in Computer Vision. It involves several subproblems, such as subject recognition, gender classification or subject verification.
Current systems of automatic face classification need a large amount of training data to robustly learn a task. However, the collection of labeled data is usually a difficult issue. For this reason, the research on methods that are able to learn from a small sized training set is essential. The dependency on the abundance of training data is not so evident in human learning processes. We are able to learn from a very small number of examples, given that we use, additionally, some prior knowledge to learn a new task. For example, we frequently find patterns and analogies from other domains to reuse them in new situations, or exploit training data from other experiences. In computer science, Multitask Learning is a new Machine Learning approach that studies this idea of knowledge transfer among different tasks, to overcome the effects of the small sample sized problem. This thesis explores, proposes and tests some Multitask Learning methods specially developed for face classification purposes. Moreover, it presents two more contributions dealing with the small sample sized problem, out of the Multitask Learning context. The first one is a method to extract external face features, to be used as an additional information source in automatic face classification problems. The second one is an empirical study on the most suitable face image resolution to perform automatic subject recognition. |
||||
| Address | Barcelona (Spain) | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Vitria;David Masip | |
| 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 | BCNPCL @ bcnpcl @ Lap2009 | Serial | 1263 | ||
| Permanent link to this record | |||||
| Author | Bogdan Raducanu; Jordi Vitria; Ales Leonardis | ||||
| Title | Online pattern recognition and machine learning techniques for computer-vision: Theory and applications | Type | Journal Article | ||
| Year | 2010 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
| Volume | 28 | Issue | 7 | Pages | 1063–1064 |
| Keywords | |||||
| Abstract | (Editorial for the Special Issue on Online pattern recognition and machine learning techniques)
In real life, visual learning is supposed to be a continuous process. This paradigm has found its way also in artificial vision systems. There is an increasing trend in pattern recognition represented by online learning approaches, which aims at continuously updating the data representation when new information arrives. Starting with a minimal dataset, the initial knowledge is expanded by incorporating incoming instances, which may have not been previously available or foreseen at the system’s design stage. An interesting characteristic of this strategy is that the train and test phases take place simultaneously. Given the increasing interest in this subject, the aim of this special issue is to be a landmark event in the development of online learning techniques and their applications with the hope that it will capture the interest of a wider audience and will attract even more researchers. We received 19 contributions, of which 9 have been accepted for publication, after having been subjected to usual peer review process. |
||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0262-8856 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RVL2010 | Serial | 1280 | ||
| Permanent link to this record | |||||
| Author | Mario Rojas; David Masip; A. Todorov; Jordi Vitria | ||||
| Title | Automatic Point-based Facial Trait Judgments Evaluation | Type | Conference Article | ||
| Year | 2010 | Publication | 23rd IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 2715–2720 | ||
| Keywords | |||||
| Abstract | Humans constantly evaluate the personalities of other people using their faces. Facial trait judgments have been studied in the psychological field, and have been determined to influence important social outcomes of our lives, such as elections outcomes and social relationships. Recent work on textual descriptions of faces has shown that trait judgments are highly correlated. Further, behavioral studies suggest that two orthogonal dimensions, valence and dominance, can describe the basis of the human judgments from faces. In this paper, we used a corpus of behavioral data of judgments on different trait dimensions to automatically learn a trait predictor from facial pixel images. We study whether trait evaluations performed by humans can be learned using machine learning classifiers, and used later in automatic evaluations of new facial images. The experiments performed using local point-based descriptors show promising results in the evaluation of the main traits. | ||||
| Address | San Francisco CA, USA | ||||
| 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 | 1063-6919 | ISBN | 978-1-4244-6984-0 | Medium | |
| Area | Expedition | Conference | CVPR | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RMT2010 | Serial | 1282 | ||
| Permanent link to this record | |||||
| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario | Type | Conference Article | ||
| Year | 2010 | Publication | 1st International Workshop on Computer Vision for Human-Robot Interaction | Abbreviated Journal | |
| Volume | Issue | Pages | 32–39 | ||
| Keywords | 1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010 | ||||
| Abstract | This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose. In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods. |
||||
| Address | San Francisco; CA; USA; June 2010 | ||||
| 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 | 2160-7508 | ISBN | 978-1-4244-7029-7 | Medium | |
| Area | Expedition | Conference | CVPRW | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DoR2010a | Serial | 1309 | ||
| Permanent link to this record | |||||
| Author | Bogdan Raducanu; D. Gatica-Perez | ||||
| Title | Inferring competitive role patterns in reality TV show through nonverbal analysis | Type | Journal Article | ||
| Year | 2012 | Publication | Multimedia Tools and Applications | Abbreviated Journal | MTAP |
| Volume | 56 | Issue | 1 | Pages | 207-226 |
| Keywords | |||||
| Abstract | This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of “The Apprentice” reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1380-7501 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RaG2012 | Serial | 1360 | ||
| Permanent link to this record | |||||
| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Person-specific face shape estimation under varying head pose from single snapshots | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 3496–3499 | ||
| Keywords | |||||
| Abstract | This paper presents a new method for person-specific face shape estimation under varying head pose of a previously unseen person from a single image. We describe a featureless approach based on a deformable 3D model and a learned face subspace. The proposed approach is based on maximizing a likelihood measure associated with a learned face subspace, which is carried out by a stochastic and genetic optimizer. We conducted the experiments on a subset of Honda Video Database showing the feasibility and robustness of the proposed approach. For this reason, our approach could lend itself nicely to complex frameworks involving 3D face tracking and face gesture recognition in monocular videos. | ||||
| Address | Istanbul, Turkey | ||||
| 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 | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DoR2010b | Serial | 1361 | ||
| Permanent link to this record | |||||
| Author | Cesar Isaza; Joaquin Salas; Bogdan Raducanu | ||||
| Title | Toward the Detection of Urban Infrastructures Edge Shadows | Type | Conference Article | ||
| Year | 2010 | Publication | 12th International Conference on Advanced Concepts for Intelligent Vision Systems | Abbreviated Journal | |
| Volume | 6474 | Issue | I | Pages | 30–37 |
| Keywords | |||||
| Abstract | In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising. | ||||
| Address | Sydney, Australia | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | eds. Blanc–Talon et al | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-17687-6 | Medium | |
| Area | Expedition | Conference | ACIVS | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ ISR2010 | Serial | 1458 | ||
| Permanent link to this record | |||||
| Author | Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez | ||||
| Title | Pattern Recognition and Image Analysis | Type | Book Whole | ||
| Year | 2011 | Publication | 5th Iberian Conference Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages | ||
| Keywords | |||||
| Abstract | |||||
| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer-Verlag | Place of Publication | Berlin | Editor | J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-2125 | Medium | ||
| Area | Expedition | Conference | IbPRIA | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | Admin @ si @ VSR2011 | Serial | 1730 | ||
| Permanent link to this record | |||||
| Author | Mario Rojas; David Masip; Jordi Vitria | ||||
| Title | Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models | Type | Conference Article | ||
| Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages | 371-378 | |
| Keywords | |||||
| Abstract | Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. | ||||
| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RMV2011a | Serial | 1731 | ||
| 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 | Admin @ si @ DoR2011 | Serial | 1751 | ||
| Permanent link to this record | |||||
| Author | Mario Rojas; David Masip; Jordi Vitria | ||||
| Title | Predicting Dominance Judgements Automatically: A Machine Learning Approach. | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE International Workshop on Social Behavior Analysis | Abbreviated Journal | |
| Volume | Issue | Pages | 939-944 | ||
| Keywords | |||||
| Abstract | The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task. | ||||
| Address | Santa Barbara, CA | ||||
| 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 | 978-1-4244-9140-7 | Medium | ||
| Area | Expedition | Conference | SBA | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RMV2011b | Serial | 1760 | ||
| Permanent link to this record | |||||
| Author | Bogdan Raducanu; Fadi Dornaika | ||||
| Title | A Discriminative Non-Linear Manifold Learning Technique for Face Recognition | Type | Book Chapter | ||
| Year | 2011 | Publication | Informatics Engineering and Information Science | Abbreviated Journal | |
| Volume | 254 | Issue | 6 | Pages | 339-353 |
| Keywords | |||||
| Abstract | In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance. |
||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1865-0929 | ISBN | 978-3-642-25482-6 | Medium | |
| Area | Expedition | Conference | ICIEIS | ||
| Notes |
OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RaD2011 | Serial | 1804 | ||
| Permanent link to this record | |||||
| Author | Mario Rojas; David Masip; A. Todorov; Jordi Vitria | ||||
| Title | Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models | Type | Journal Article | ||
| Year | 2011 | Publication | PloS one | Abbreviated Journal | Plos |
| Volume | 6 | Issue | 8 | Pages | e23323 |
| Keywords | |||||
| Abstract | JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions |
||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Public Library of Science | 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 |
OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RMT2011 | Serial | 1883 | ||
| Permanent link to this record | |||||