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| Author | Albert Clapes; Miguel Reyes; Sergio Escalera | ||||
| Title | User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis | Type | Conference Article | ||
| Year | 2012 | Publication | 7th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
| Volume | 7378 | Issue | Pages | 1-11 | |
| Keywords | |||||
| Abstract | We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. | ||||
| Address | Mallorca | ||||
| 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 | 978-3-642-31566-4 | Medium | |
| Area | Expedition | Conference | AMDO | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ CRE2012 | Serial | 2010 | ||
| Permanent link to this record | |||||
| Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
| Title | Evaluation of Similarity Functions in Multimodal Stereo | Type | Conference Article | ||
| Year | 2012 | Publication | 9th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 7324 | Issue | I | Pages | 320-329 |
| Keywords | Aveiro, Portugal | ||||
| Abstract | This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head. | ||||
| Address | |||||
| 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 | 978-3-642-31294-6 | Medium | |
| Area | Expedition | Conference | ICIAR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | BLS2012a | Serial | 2014 | ||
| Permanent link to this record | |||||
| Author | Miguel Oliveira; Angel Sappa; V. Santos | ||||
| Title | Color Correction using 3D Gaussian Mixture Models | Type | Conference Article | ||
| Year | 2012 | Publication | 9th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 7324 | Issue | I | Pages | 97-106 |
| Keywords | |||||
| Abstract | The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. | ||||
| Address | |||||
| 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 | 10.1007/978-3-642-31295-3_12 | Medium | |
| Area | Expedition | Conference | ICIAR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ OSS2012a | Serial | 2015 | ||
| Permanent link to this record | |||||
| Author | Jose Manuel Alvarez; Theo Gevers; Y. LeCun; Antonio Lopez | ||||
| Title | Road Scene Segmentation from a Single Image | Type | Conference Article | ||
| Year | 2012 | Publication | 12th European Conference on Computer Vision | Abbreviated Journal | |
| Volume | 7578 | Issue | VII | Pages | 376-389 |
| Keywords | road detection | ||||
| Abstract | Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes provides relevant contextual information to improve their understanding.
In this paper, we use a convolutional neural network based algorithm to learn features from noisy labels to recover the 3D scene layout of a road image. The novelty of the algorithm relies on generating training labels by applying an algorithm trained on a general image dataset to classify on–board images. Further, we propose a novel texture descriptor based on a learned color plane fusion to obtain maximal uniformity in road areas. Finally, acquired (off–line) and current (on–line) information are combined to detect road areas in single images. From quantitative and qualitative experiments, conducted on publicly available datasets, it is concluded that convolutional neural networks are suitable for learning 3D scene layout from noisy labels and provides a relative improvement of 7% compared to the baseline. Furthermore, combining color planes provides a statistical description of road areas that exhibits maximal uniformity and provides a relative improvement of 8% compared to the baseline. Finally, the improvement is even bigger when acquired and current information from a single image are combined |
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| Address | Florence, Italy | ||||
| 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 | 978-3-642-33785-7 | Medium | |
| Area | Expedition | Conference | ECCV | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | Admin @ si @ AGL2012; ADAS @ adas @ agl2012a | Serial | 2022 | ||
| Permanent link to this record | |||||
| Author | Ivo Everts; Jan van Gemert; Theo Gevers | ||||
| Title | Per-patch Descriptor Selection using Surface and Scene Properties | Type | Conference Article | ||
| Year | 2012 | Publication | 12th European Conference on Computer Vision | Abbreviated Journal | |
| Volume | 7577 | Issue | VI | Pages | 172-186 |
| Keywords | |||||
| Abstract | Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool. | ||||
| Address | Florence, Italy | ||||
| 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 | 978-3-642-33782-6 | Medium | |
| Area | Expedition | Conference | ECCV | ||
| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ EGG2012 | Serial | 2023 | ||
| Permanent link to this record | |||||
| Author | Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah | ||||
| Title | Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles | Type | Conference Article | ||
| Year | 2012 | Publication | 12th European Conference on Computer Vision | Abbreviated Journal | |
| Volume | 7574 | Issue | III | Pages | 525-538 |
| Keywords | |||||
| Abstract | Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics. | ||||
| Address | Florence, Italy | ||||
| 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 | 978-3-642-33711-6 | Medium | |
| Area | Expedition | Conference | ECCV | ||
| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ DGS2012 | Serial | 2024 | ||
| Permanent link to this record | |||||
| Author | Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca | ||||
| Title | A New Image Dataset on Human Interactions | Type | Conference Article | ||
| Year | 2012 | Publication | 7th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
| Volume | 7378 | Issue | Pages | 204-209 | |
| Keywords | |||||
| Abstract | This article describes a new collection of still image dataset which are dedicated to interactions between people. Human action recognition from still images have been a hot topic recently, but most of them are actions performed by a single person, like running, walking, riding bikes, phoning and so on and there is no interactions between people in one image. The dataset collected in this paper are concentrating on human interaction between two people aiming to explore this new topic in the research area of action recognition from still images. | ||||
| Address | Mallorca | ||||
| 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 | 978-3-642-31566-4 | Medium | |
| Area | Expedition | Conference | AMDO | ||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ GGT2012 | Serial | 2030 | ||
| Permanent link to this record | |||||
| Author | Ekaterina Zaytseva; Santiago Segui; Jordi Vitria | ||||
| Title | Sketchable Histograms of Oriented Gradients for Object Detection | Type | Conference Article | ||
| Year | 2012 | Publication | 17th Iberomerican Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | 7441 | Issue | Pages | 374-381 | |
| Keywords | |||||
| Abstract | In this paper we investigate a new representation approach for visual object recognition. The new representation, called sketchable-HoG, extends the classical histogram of oriented gradients (HoG) feature by adding two different aspects: the stability of the majority orientation and the continuity of gradient orientations. In this way, the sketchable-HoG locally characterizes the complexity of an object model and introduces global structure information while still keeping simplicity, compactness and robustness. We evaluated the proposed image descriptor on publicly Catltech 101 dataset. The obtained results outperforms classical HoG descriptor as well as other reported descriptors in the literature. | ||||
| Address | Buenos Aires, Argentina | ||||
| 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 | 978-3-642-33274-6 | Medium | |
| Area | Expedition | Conference | CIARP | ||
| Notes | OR; MILAB;MV | Approved | no | ||
| Call Number | Admin @ si @ ZSV2012 | Serial | 2048 | ||
| Permanent link to this record | |||||
| Author | Volkmar Frinken; Alicia Fornes; Josep Llados; Jean-Marc Ogier | ||||
| Title | Bidirectional Language Model for Handwriting Recognition | Type | Conference Article | ||
| Year | 2012 | Publication | Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop | Abbreviated Journal | |
| Volume | 7626 | Issue | Pages | 611-619 | |
| Keywords | |||||
| Abstract | In order to improve the results of automatically recognized handwritten text, information about the language is commonly included in the recognition process. A common approach is to represent a text line as a sequence. It is processed in one direction and the language information via n-grams is directly included in the decoding. This approach, however, only uses context on one side to estimate a word’s probability. Therefore, we propose a bidirectional recognition in this paper, using distinct forward and a backward language models. By combining decoding hypotheses from both directions, we achieve a significant increase in recognition accuracy for the off-line writer independent handwriting recognition task. Both language models are of the same type and can be estimated on the same corpus. Hence, the increase in recognition accuracy comes without any additional need for training data or language modeling complexity. | ||||
| Address | Japan | ||||
| 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 | 978-3-642-34165-6 | Medium | |
| Area | Expedition | Conference | SSPR&SPR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FFL2012 | Serial | 2057 | ||
| Permanent link to this record | |||||
| Author | Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez | ||||
| Title | Moving object detection from mobile platforms using stereo data registration | Type | Book Chapter | ||
| Year | 2012 | Publication | Computational Intelligence paradigms in advanced pattern classification | Abbreviated Journal | |
| Volume | 386 | Issue | Pages | 25-37 | |
| Keywords | pedestrian detection | ||||
| Abstract | This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher |
Springer Berlin Heidelberg | Place of Publication | Editor | Marek R. Ogiela; Lakhmi C. Jain | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1860-949X | ISBN | 978-3-642-24048-5 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ SGD2012 | Serial | 2061 | ||
| Permanent link to this record | |||||
| Author | Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez | ||||
| Title | Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance | Type | Book Chapter | ||
| Year | 2012 | Publication | Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence | Abbreviated Journal | |
| Volume | 384 | Issue | 3 | Pages | 87-95 |
| Keywords | |||||
| Abstract | The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally. | ||||
| 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 | 1860-949X | ISBN | 978-3-642-24033-1 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ BFR2012 | Serial | 2062 | ||
| Permanent link to this record | |||||
| Author | Miguel Angel Bautista; Antonio Hernandez; Victor Ponce; Xavier Perez Sala; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera | ||||
| Title | Probability-based Dynamic TimeWarping for Gesture Recognition on RGB-D data | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis | Abbreviated Journal | |
| Volume | 7854 | Issue | Pages | 126-135 | |
| Keywords | |||||
| Abstract | Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost below a certain threshold is found within the test sequence. Nevertheless, either taking one single sample per gesture category or a set of isolated samples may not encode the variability of such gesture category. In this paper, a probability-based DTW for gesture recognition is proposed. Different samples of the same gesture pattern obtained from RGB-Depth data are used to build a Gaussian-based probabilistic model of the gesture. Finally, the cost of DTW has been adapted accordingly to the new model. The proposed approach is tested in a challenging scenario, showing better performance of the probability-based DTW in comparison to state-of-the-art approaches for gesture recognition on RGB-D data. | ||||
| 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 | 0302-9743 | ISBN | 978-3-642-40302-6 | Medium | |
| Area | Expedition | Conference | WDIA | ||
| Notes | MILAB; OR;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ BHP2012 | Serial | 2120 | ||
| Permanent link to this record | |||||
| Author | Miguel Reyes; Albert Clapes; Luis Felipe Mejia; Jose Ramirez; Juan R Revilla; Sergio Escalera | ||||
| Title | Posture Analysis and Range of Movement Estimation using Depth Maps | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis | Abbreviated Journal | |
| Volume | 7854 | Issue | Pages | 97-105 | |
| Keywords | |||||
| Abstract | World Health Organization estimates that 80% of the world population is affected of back pain during his life. Current practices to analyze back problems are expensive, subjective, and invasive. In this work, we propose a novel tool for posture and range of movement estimation based on the analysis of 3D information from depth maps. Given a set of keypoints defined by the user, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matching using a novel point-to-point fitting procedure, and accurate measurements about posture, spinal curvature, and range of movement are computed. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent musculoskeletal disorders, such as back pain, as well as tracking the posture evolution of patients in rehabilitation treatments. | ||||
| 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 | 0302-9743 | ISBN | 978-3-642-40302-6 | Medium | |
| Area | Expedition | Conference | WDIA | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ RCM2012 | Serial | 2121 | ||
| Permanent link to this record | |||||
| Author | Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados | ||||
| Title | Hierarchical graph representation for symbol spotting in graphical document images | Type | Conference Article | ||
| Year | 2012 | Publication | Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop | Abbreviated Journal | |
| Volume | 7626 | Issue | Pages | 529-538 | |
| Keywords | |||||
| Abstract | Symbol spotting can be defined as locating given query symbol in a large collection of graphical documents. In this paper we present a hierarchical graph representation for symbols. This representation allows graph matching methods to deal with low-level vectorization errors and, thus, to perform a robust symbol spotting. To show the potential of this approach, we conduct an experiment with the SESYD dataset. | ||||
| Address | Miyajima-Itsukushima, Hiroshima | ||||
| 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 | 978-3-642-34165-6 | Medium | |
| Area | Expedition | Conference | SSPR&SPR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ BDJ2012 | Serial | 2126 | ||
| Permanent link to this record | |||||
| Author | David Masip; Alexander Todorov; Jordi Vitria | ||||
| Title | The Role of Facial Regions in Evaluating Social Dime | Type | Conference Article | ||
| Year | 2012 | Publication | 12th European Conference on Computer Vision – Workshops and Demonstrations | Abbreviated Journal | |
| Volume | 7584 | Issue | II | Pages | 210-219 |
| Keywords | Workshops and Demonstrations | ||||
| Abstract | Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics. | ||||
| Address | Florence, Italy | ||||
| Corporate Author | Thesis | ||||
| Publisher |
Springer Berlin Heidelberg | Place of Publication | Editor | Andrea Fusiello, Vittorio Murino, Rita Cucchiara | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-33867-0 | Medium | |
| Area | Expedition | Conference | ECCVW | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ MTV2012 | Serial | 2171 | ||
| Permanent link to this record | |||||