Contributions to High-Dimensional Pattern Recognition

This thesis gathers some contributions to statistical pattern recognition particularly targeted at problems in which the feature vectors are high-dimensional. Three pattern recognition scenarios are addressed, namely pattern classification, regression analysis and score fusion. For each of these, an algorithm for learning a statistical model is presented. In order to address the difficulty that is encountered when the feature vectors are high-dimensional, adequate models and objective functions are defined. The strategy of learning simultaneously a dimensionality reduction function and the pattern recognition model parameters is shown to be quite effective, making it possible to learn the model without discarding any discriminative information. Another topic that is addressed in the thesis is the use of tangent vectors as a way to take better advantage of the available training data. Using this idea, two popular discriminative dimensionality reduction techniques are shown to be effectively improved. For each of the algorithms proposed throughout the thesis, several data sets are used to illustrate the properties and the performance of the approaches. The empirical results show that the proposed techniques perform considerably well, and furthermore the models learned tend to be very computationally efficient.Villegas Santamaría, M. (2011). Contributions to High-Dimensional Pattern Recognition [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10939Palanci

Face Analysis and Recognition in Mobile Devices

Face recognition is currently a very active research topic due to the great variety of applications it can offer. Moreover, nowadays is very common for people to have mobile devices such as PDAs or mobile phones which have an integrated digital camera. This gives the opportunity to develop face recognition applications for this type of devices. This thesis treats the problem of face analysis and recognition in mobile devices. The problem is discussed and analyzed, observing which are the difficulties that are encountered. Some algorithms for face recognition are analyzed and optimized so that they are better suited for the constrains of mobile devices. An implementation of the algorithms in J2ME are presented, and these are used to create a demonstration application that works in commercial phones.Villegas Santamaría, M. (2008). Face Analysis and Recognition in Mobile Devices. http://hdl.handle.net/10251/13013Archivo delegad

On improving robustness of LDA and SRDA by using tangent vectors

This is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Letters, [Volume 34, Issue 9, 1 July 2013, Pages 1094–1100] DOI: 10.1016/j.patrec.2013.03.001[EN] In the area of pattern recognition, it is common for few training samples to be available with respect to the dimensionality of the representation space; this is known as the curse of dimensionality. This problem can be alleviated by using a dimensionality reduction approach, which overcomes the curse relatively well. Moreover, supervised dimensionality reduction techniques generally provide better recognition performance; however, several of these tend to suffer from the curse when applied directly to high-dimensional spaces. We propose to overcome this problem by incorporating additional information to supervised subspace learning techniques using what is known as tangent vectors. This additional information accounts for the possible differences that the sample data can suffer. In fact, this can be seen as a way to model the unseen data and make better use of the scarce training samples. In this paper, methods for incorporating tangent vector information are described for one classical technique (LDA) and one state-of-the-art technique (SRDA). Experimental results confirm that this additional information improves performance and robustness to known transformations.Work partially supported through the EU 7th Framework Programme grant tranScriptorium (Ref: 600707), by the Spanish MEC under the STraDA research project (TIN2012-37475-C02-01) and by the Generalitat Valenciana under grant Prometeo/2009/014.Villegas Santamaría, M.; Paredes Palacios, R. (2013). On improving robustness of LDA and SRDA by using tangent vectors. Pattern Recognition Letters. 34(9):1094-1100. https://doi.org/10.1016/j.patrec.2013.03.0011094110034

Overview of the ImageCLEF 2014 Scalable Concept Image Annotation Task

[EN] The ImageCLEF 2014 Scalable Concept Image Annotation task was the third edition of a challenge aimed at developing more scalable image annotation systems. Unlike traditional image annotation challenges, which rely on a set of manually annotated images as training data, the participants were only allowed to use data and/or resources that as new concepts to detect are introduced do not require significant human effort (such as hand labeling). The participants were provided with web data consisting of 500,000 images, which included textual features obtained from the web pages on which the images appeared, as well as various visual features extracted from the images themselves. To optimize their systems, the participants were provided with a development set of 1,940 samples and its corresponding hand labeled ground truth for 107 concepts. The performance of the submissions was measured using a test set of 7,291 samples which was hand labeled for 207 concepts among which 100 were new concepts unseen during development. In total 11 teams participated in the task submitting overall 58 system runs. Thanks to the larger amount of unseen concepts in the results the generalization of the systems has been more clearly observed and thus demonstrating the potential for scalability.The authors are very grateful with the CLEF initiative for supporting Image CLEF.The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under the tranScriptorium project (#600707) and from the Spanish MEC under the STraDA project (TIN2012-37475-C02-01).Villegas Santamaría, M.; Paredes Palacios, R. (2014). Overview of the ImageCLEF 2014 Scalable Concept Image Annotation Task. CEUR Workshop Proceedings. 1180:308-328. http://hdl.handle.net/10251/61152S308328118

Relevant clouds: leveraging relevance feedback to build tag clouds for image search

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40802-1_18Previous work in the literature has been aimed at exploring tag clouds to improve image search and potentially increase retrieval performance. However, to date none has considered the idea of building tag clouds derived from relevance feedback. We propose a simple approach to such an idea, where the tag cloud gives more importance to the words from the relevant images than the non-relevant ones. A preliminary study with 164 queries inspected by 14 participants over a 30M dataset of automatically annotated images showed that 1) tag clouds derived this way are found to be informative: users considered roughly 20% of the presented tags to be relevant for any query at any time; and 2) the importance given to the tags correlates with user judgments: tags ranked in the first positions tended to be perceived more often as relevant to the topic that users had in mind.Work supported by EU FP7/2007-2013 under grant agreements 600707 (tranScriptorium) and 287576 (CasMaCat), and by the STraDA project (TIN2012-37475-C02-01).Leiva Torres, LA.; Villegas Santamaría, M.; Paredes Palacios, R. (2013). Relevant clouds: leveraging relevance feedback to build tag clouds for image search. En Information Access Evaluation. Multilinguality, Multimodality, and Visualization. Springer Verlag (Germany). 143-149. https://doi.org/10.1007/978-3-642-40802-1_18S143149Begelman, G., Keller, P., Smadja, F.: Automated tag clustering: Improving search and exploration in the tag space. In: Collaborative Web Tagging (2006)Callegari, J., Morreale, P.: Assessment of the utility of tag clouds for faster image retrieval. In: Proc. MIR (2010)Ganchev, K., Hall, K., McDonald, R., Petrov, S.: Using search-logs to improve query tagging. In: Proc. ACL (2012)Hassan-Montero, Y., Herrero-Solana, V.: Improving tag-clouds as visual information retrieval interfaces. In: Proc. InSciT (2006)Leiva, L.A., Villegas, M., Paredes, R.: Query refinement suggestion in multimodal interactive image retrieval. In: Proc. ICMI (2011)Liu, D., Hua, X.-S., Yang, L., Wang, M., Zhang, H.-J.: Tag ranking. In: Proc. WWW (2009)Overell, S., Sigurbjörnsson, B., van Zwol, R.: Classifying tags using open content resources. In: Proc. WSDM (2009)Rui, Y., Huang, T.S., Ortega, M., Mehrotra, S.: Relevance feedback: A power tool for interactive content-based image retrieval. T. Circ. Syst. Vid. 8(5) (1998)Sigurbjörnsson, B., van Zwol, R.: Flickr tag recommendation based on collective knowledge. In: Proc. WWW (2008)Trattner, C., Lin, Y.-L., Parra, D., Yue, Z., Real, W., Brusilovsky, P.: Evaluating tag-based information access in image collections. In: Proc. HT (2012)Villegas, M., Paredes, R.: Image-text dataset generation for image annotation and retrieval. In: Proc. CERI (2012)Zhang, C., Chai, J.Y., Jin, R.: User term feedback in interactive text-based image retrieval. In: Proc. SIGIR (2005

Design of a hydrokinetic turbine capable of satisfying electricity demand for housing on the margin of the Magdalena river through analysis by finite elements

This research is aimed to design a hydrokinetic turbine for electric generation taking advantage of available energy of the Magdalena River, which has a great flow near to its mouth in the Atlantic Ocean of Northern Colombian. The turbine design consists of a tri-bladed horizontal axis turbine totally submerged; the rotor is fixed to a metallic platform with tanks acting as floats. It also contains an asynchronous electric engine as a generator and electrical lines. The turbine power shaft is transmitted to the engine by a system of toothed belts, which performs the role of gearbox and multiplier. As a result, CFD simulations shows several variables of interest in order to evaluate power generation, such as torque, angular velocity, power, turbine efficiency, and hydrokinetic and structural analysis are obtained by means of finite elements.Universidad Autónoma del Caribe, Universidad De La Costa

COMPARISON OF ILLUMINATION NORMALIZATION METHODS FOR FACE RECOGNITION

Illumination invariance is one of the most difficult properties to achieve in a face recognition system. Illumination normalization is a way to solve this problem. In this paper we compare several illumination normalization techniques, including traditional and proposed ones. An error rate less than 1 % is achieved using the Yale Face Database B. 1

Switching TNF antagonists in patients with chronic arthritis: An observational study of 488 patients over a four-year period

The objective of this work is to analyze the survival of infliximab, etanercept and adalimumab in patients who have switched among tumor necrosis factor (TNF) antagonists for the treatment of chronic arthritis. BIOBADASER is a national registry of patients with different forms of chronic arthritis who are treated with biologics. Using this registry, we have analyzed patient switching of TNF antagonists. The cumulative discontinuation rate was calculated using the actuarial method. The log-rank test was used to compare survival curves, and Cox regression models were used to assess independent factors associated with discontinuing medication. Between February 2000 and September 2004, 4,706 patients were registered in BIOBADASER, of whom 68% had rheumatoid arthritis, 11% ankylosing spondylitis, 10% psoriatic arthritis, and 11% other forms of chronic arthritis. One- and two-year drug survival rates of the TNF antagonist were 0.83 and 0.75, respectively. There were 488 patients treated with more than one TNF antagonist. In this situation, survival of the second TNF antagonist decreased to 0.68 and 0.60 at 1 and 2 years, respectively. Survival was better in patients replacing the first TNF antagonist because of adverse events (hazard ratio (HR) for discontinuation 0.55 (95% confidence interval (CI), 0.34-0.84)), and worse in patients older than 60 years (HR 1.10 (95% CI 0.97-2.49)) or who were treated with infliximab (HR 3.22 (95% CI 2.13-4.87)). In summary, in patients who require continuous therapy and have failed to respond to a TNF antagonist, replacement with a different TNF antagonist may be of use under certain situations. This issue will deserve continuous reassessment with the arrival of new medications. © 2006 Gomez-Reino and Loreto Carmona; licensee BioMed Central Ltd