|
Petia Radeva, & Jordi Vitria. (2004). Discriminant Projections Embedding for Nearest Neighbor Classification.
|
|
|
Petia Radeva, & Jordi Vitria. (2003). “Inteligencia artificial” Centre de Visio per Computador.
|
|
|
Petia Radeva, & Jordi Vitria. (2001). Region-Based Approach for Discriminant Snakes.
|
|
|
Petia Radeva, & M. Scoccianti. (2000). 3D Reconstruction of Abdominal Aortic Aneurysm.
|
|
|
Petia Radeva, & Enric Marti. (1995). Facial Features Segmentation by Model-Based Snakes..
|
|
|
Bogdan Raducanu, & D. Gatica-Perez. (2012). Inferring competitive role patterns in reality TV show through nonverbal analysis. MTAP - Multimedia Tools and Applications, 56(1), 207–226.
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.
|
|
|
Bogdan Raducanu, & Fadi Dornaika. (2010). Dynamic Facial Expression Recognition Using Laplacian Eigenmaps-Based Manifold Learning. In IEEE International Conference on Robotics and Automation (156–161).
Abstract: In this paper, we propose an integrated framework for tracking, modelling and recognition of facial expressions. The main contributions are: (i) a view- and texture independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker; (ii) the complexity of the non-linear facial expression space is modelled through a manifold, whose structure is learned using Laplacian Eigenmaps. The projected facial expressions are afterwards recognized based on Nearest Neighbor classifier; (iii) with the proposed approach, we developed an application for an AIBO robot, in which it mirrors the perceived facial expression.
|
|
|
Bogdan Raducanu, & Fadi Dornaika. (2009). Natural Facial Expression Recognition Using Dynamic and Static Schemes. In 5th International Symposium on Visual Computing (Vol. 5875, 730–739). LNCS. Springer Berlin Heidelberg.
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.
|
|
|
Bogdan Raducanu, & Fadi Dornaika. (2008). Dynamic Vs. Static Recognition of Facial Expressions. In Rabuñal (Ed.), Ambient Intelligence. European Conference (Vol. 5355, 13–25). LNCS.
|
|
|
Petia Radeva. (2003). On the Role of Intravascular Ultrasound Image Analysis.
|
|
|
Petia Radeva. (1993). Segmentacion de Imagenes Radiograficas con Snakes. Aplicacion a la Determinacion de la Madurez Osea..
|
|
|
Petia Radeva. (1993). A Rule-Based Approach to Hand X-Ray image Segmentation..
|
|
|
A. Pujol, Jordi Vitria, Petia Radeva, Xavier Binefa, Robert Benavente, Ernest Valveny, et al. (1999). Real time pharmaceutical product recognition using color and shape indexing. In Proceedings of the 2nd International Workshop on European Scientific and Industrial Collaboration (WESIC´99), Promotoring Advanced Technologies in Manufacturing..
|
|
|
Oriol Pujol, & Petia Radeva. (2005). Solving Particularization with Supervised Clustering Competition Scheme. In Pattern Recognition and Image Analysis (IbPRIA 2005), LNCS 3523: 11–18.
|
|
|
Oriol Pujol, & Petia Radeva. (2005). On the assessment of texture descriptors in intravascular ultrasound images: A boosting approach to a feasible plaque classification. In Plaque Imaging: Pixel to Molecular Level, IOS Press, J. Suri et al. (Eds.), 113: 276–299, ISBN: 1–58603–516–9.
|
|