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Author |
Joan Mas |
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
A Syntactic Pattern Recognition Approach based on a Distribution Tolerant Adjacency Grammar and a Spatial Indexed Parser. Application to Sketched Document Recognition |
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2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Sketch recognition is a discipline which has gained an increasing interest in the last
20 years. This is due to the appearance of new devices such as PDA, Tablet PC’s
or digital pen & paper protocols. From the wide range of sketched documents we
focus on those that represent structured documents such as: architectural floor-plans,
engineering drawing, UML diagrams, etc. To recognize and understand these kinds
of documents, first we have to recognize the different compounding symbols and then
we have to identify the relations between these elements. From the way that a sketch
is captured, there are two categories: on-line and off-line. On-line input modes refer
to draw directly on a PDA or a Tablet PC’s while off-line input modes refer to scan
a previously drawn sketch.
This thesis is an overlapping of three different areas on Computer Science: Pattern
Recognition, Document Analysis and Human-Computer Interaction. The aim of this
thesis is to interpret sketched documents independently on whether they are captured
on-line or off-line. For this reason, the proposed approach should contain the following
features. First, as we are working with sketches the elements present in our input
contain distortions. Second, as we would work in on-line or off-line input modes, the
order in the input of the primitives is indifferent. Finally, the proposed method should
be applied in real scenarios, its response time must be slow.
To interpret a sketched document we propose a syntactic approach. A syntactic
approach is composed of two correlated components: a grammar and a parser. The
grammar allows describing the different elements on the document as well as their
relations. The parser, given a document checks whether it belongs to the language
generated by the grammar or not. Thus, the grammar should be able to cope with
the distortions appearing on the instances of the elements. Moreover, it would be
necessary to define a symbol independently of the order of their primitives. Concerning to the parser when analyzing 2D sentences, it does not assume an order in the
primitives. Then, at each new primitive in the input, the parser searches among the
previous analyzed symbols candidates to produce a valid reduction.
Taking into account these features, we have proposed a grammar based on Adjacency Grammars. This kind of grammars defines their productions as a multiset
of symbols rather than a list. This allows describing a symbol without an order in
their components. To cope with distortion we have proposed a distortion model.
This distortion model is an attributed estimated over the constraints of the grammar and passed through the productions. This measure gives an idea on how far is the
symbol from its ideal model. In addition to the distortion on the constraints other
distortions appear when working with sketches. These distortions are: overtracing,
overlapping, gaps or spurious strokes. Some grammatical productions have been defined to cope with these errors. Concerning the recognition, we have proposed an
incremental parser with an indexation mechanism. Incremental parsers analyze the
input symbol by symbol given a response to the user when a primitive is analyzed.
This makes incremental parser suitable to work in on-line as well as off-line input
modes. The parser has been adapted with an indexation mechanism based on a spatial division. This indexation mechanism allows setting the primitives in the space
and reducing the search to a neighbourhood.
A third contribution is a grammatical inference algorithm. This method given a
set of symbols captures the production describing it. In the field of formal languages,
different approaches has been proposed but in the graphical domain not so much work
is done in this field. The proposed method is able to capture the production from
a set of symbol although they are drawn in different order. A matching step based
on the Haussdorff distance and the Hungarian method has been proposed to match
the primitives of the different symbols. In addition the proposed approach is able to
capture the variability in the parameters of the constraints.
From the experimental results, we may conclude that we have proposed a robust
approach to describe and recognize sketches. Moreover, the addition of new symbols
to the alphabet is not restricted to an expert. Finally, the proposed approach has
been used in two real scenarios obtaining a good performance. |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Gemma Sanchez;Josep Llados |
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978-84-937261-4-0 |
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DAG |
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no |
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Call Number |
DAG @ dag @ Mas2010 |
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1334 |
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Author |
Francisco Javier Orozco |
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
Human Emotion Evaluation on Facial Image Sequences |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Psychological evidence has emphasized the importance of affective behaviour understanding due to its high impact in nowadays interaction humans and computers. All
type of affective and behavioural patterns such as gestures, emotions and mental
states are highly displayed through the face, head and body. Therefore, this thesis is
focused to analyse affective behaviours on head and face. To this end, head and facial
movements are encoded by using appearance based tracking methods. Specifically,
a wise combination of deformable models captures rigid and non-rigid movements of
different kinematics; 3D head pose, eyebrows, mouth, eyelids and irises are taken into
account as basis for extracting features from databases of video sequences. This approach combines the strengths of adaptive appearance models, optimization methods
and backtracking techniques.
For about thirty years, computer sciences have addressed the investigation on
human emotions to the automatic recognition of six prototypic emotions suggested
by Darwin and systematized by Paul Ekman in the seventies. The Facial Action
Coding System (FACS) which uses discrete movements of the face (called Action
units or AUs) to code the six facial emotions named anger, disgust, fear, happy-Joy,
sadness and surprise. However, human emotions are much complex patterns that
have not received the same attention from computer scientists.
Simon Baron-Cohen proposed a new taxonomy of emotions and mental states
without a system coding of the facial actions. These 426 affective behaviours are
more challenging for the understanding of human emotions. Beyond of classically
classifying the six basic facial expressions, more subtle gestures, facial actions and
spontaneous emotions are considered here. By assessing confidence on the recognition
results, exploring spatial and temporal relationships of the features, some methods are
combined and enhanced for developing new taxonomy of expressions and emotions.
The objective of this dissertation is to develop a computer vision system, including both facial feature extraction, expression recognition and emotion understanding
by building a bottom-up reasoning process. Building a detailed taxonomy of human
affective behaviours is an interesting challenge for head-face-based image analysis
methods. In this paper, we exploit the strengths of Canonical Correlation Analysis
(CCA) to enhance an on-line head-face tracker. A relationship between head pose and
local facial movements is studied according to their cognitive interpretation on affective expressions and emotions. Active Shape Models are synthesized for AAMs based
on CCA-regression. Head pose and facial actions are fused into a maximally correlated space in order to assess expressiveness, confidence and classification in a CBR system. The CBR solutions are also correlated to the cognitive features, which allow
avoiding exhaustive search when recognizing new head-face features. Subsequently,
Support Vector Machines (SVMs) and Bayesian Networks are applied for learning the
spatial relationships of facial expressions. Similarly, the temporal evolution of facial
expressions, emotion and mental states are analysed based on Factorized Dynamic
Bayesian Networks (FaDBN).
As results, the bottom-up system recognizes six facial expressions, six basic emotions and six mental states, plus enhancing this categorization with confidence assessment at each level, intensity of expressions and a complete taxonomy |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Jordi Gonzalez;Xavier Roca |
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978-84-936529-3-7 |
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no |
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Call Number |
Admin @ si @ Oro2010 |
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1335 |
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Author |
Marc Serra |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Estimating Intrinsic Images from Physical and Categorical Color Cues |
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Report |
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Year |
2010 |
Publication |
CVC Technical Report |
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Volume |
151 |
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Master's thesis |
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CIC |
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no |
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Call Number |
Admin @ si @ Ser2010 |
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1345 |
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Author |
Ahmed Mounir Gad |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Object Localization Enhancement by Multiple Segmentation Fusion |
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Report |
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Year |
2010 |
Publication |
CVC Technical Report |
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152 |
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Admin @ si @ Mou2010 |
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1346 |
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Author |
Antonio Hernandez |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Pose and Face Recovery via Spatio-temporal GrabCut Human Segmentation |
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Report |
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2010 |
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CVC Technical Report |
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153 |
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HUPBA;MILAB |
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no |
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Call Number |
Admin @ si @ Her2010 |
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1347 |
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Author |
Jorge Bernal; Fernando Vilariño; F. Javier Sanchez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Feature Detectors and Feature Descriptors: Where We Are Now |
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Report |
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2010 |
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CVC Technical Report |
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154 |
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Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours. |
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MV;SIAI |
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Admin @ si @ BVS2010; IAM @ iam @ BVS2010 |
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1348 |
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Author |
Lluis Pere de las Heras |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Syntactic Model for Semantic Document Analysis |
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Report |
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2010 |
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CVC Technical Report |
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158 |
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Admin @ si @ Per2010 |
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1350 |
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Author |
Anjan Dutta |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Symbol Spotting in Graphical Documents by Serialized Subgraph Matching |
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2010 |
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CVC Technical Report |
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159 |
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no |
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Admin @ si @ Dut2010 |
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1351 |
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Author |
Ekain Artola |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Human Attention Map Prediction Combining Visual Features |
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2010 |
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CVC Technical Report |
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160 |
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Bachelor's thesis |
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Admin @ si @ Art2010 |
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1352 |
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Author |
David Fernandez |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Handwritten Word Spotting in Old Manuscript Images using Shape Descriptors |
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2010 |
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CVC Technical Report |
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161 |
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DAG |
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Admin @ si @ Fer2010b |
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1353 |
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Author |
Jon Almazan |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
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2010 |
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CVC Technical Report |
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163 |
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Admin @ si @ Alm2010 |
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1354 |
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Author |
Nataliya Shapovalova |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
On Importance of Interaction and Context |
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2010 |
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CVC Technical Report |
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155 |
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Admin @ si @ Sha2010 |
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1355 |
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Author |
Zhanwu Xiong |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
A Pompd Model for Active Camera Control |
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2010 |
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CVC Technical Report |
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156 |
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ISE |
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Admin @ si @ Xio2010 |
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1356 |
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Author |
David Geronimo; Antonio Lopez |
![goto web page url](img/www.gif)
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Title |
Deteccion de Peatones para Sistemas Avanzados de Asistencia al Conductor |
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Miscellaneous |
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2010 |
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UAB Divulga |
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Los sistemas de asistencia al conductor, y particularmente los sistemas de protección de peatones, representan uno de los campos de investigación más activos dedicados a la mejora de la seguridad vial. El mayor desafío es el desarrollo de sistemas a bordo fiables de detección de peatones. En esta revisión del estado de la técnica de la detección de peatones, se divide el problema en diferentes etapas, cada una con responsabilidades propias dentro del sistema. Esta división facilita el posterior análisis y discusión de cada uno de los métodos en la literatura, favoreciendo la comparación entre ellos. Finalmente se discuten los temas más importantes de este campo poniendo especial énfasis en las necesidades actuales y los desafíos futuros. |
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Bellaterra (Catalonia), Spain |
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spreading;ADAS |
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ADAS @ adas @ GeL2010a |
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1414 |
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Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu |
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Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks |
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2010 |
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12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. |
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Social interaction; Multimodal fusion, Influence model; Social network analysis |
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Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters
are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented
mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states
encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results
are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network. |
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Beijing (China) |
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ICMI-MLI |
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OR;MILAB;HUPBA;MV |
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BCNPCL @ bcnpcl @ ERV2010 |
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1427 |
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