Active Foreground Region Extraction and Tracking for Sports Video Annotation

Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.

Applying logic forms and statistical methods to CL-SR performance

This paper describes a CL-SR system that employs two different techniques: the first one is based on NLP rules that consist on applying logic forms to the topic processing while the second one basically consists on applying the IR-n statistical search engine to the spoken document collection. The application of logic forms to the topics allows to increase the weight of topic terms according to a set of syntactic rules. Thus, the weights of the topic terms are used by IR-n system in the information retrieval process.

3D Feature Extraction and Modelling for SLAM

Paper submitted to the 39th International Symposium on Robotics ISR 2008, Seoul, South Korea, October 15-17, 2008.

Computational approaches to subjectivity and sentiment analysis: Present and envisaged methods and applications

Recent years have witnessed a surge of interest in computational methods for affect, ranging from opinion mining, to subjectivity detection, to sentiment and emotion analysis. This article presents a brief overview of the latest trends in the field and describes the manner in which the articles contained in the special issue contribute to the advancement of the area. Finally, we comment on the current challenges and envisaged developments of the subjectivity and sentiment analysis fields, as well as their application to other Natural Language Processing tasks and related domains.

Functionalization of carbon nanotubes using aminobenzene acids and electrochemical methods. Electroactivity for the oxygen reduction reaction

Functionalized carbon nanotubes (CNTs) using three aminobenzene acids with different functional groups (carboxylic, sulphonic, phosphonic) in para position have been synthesized through potentiodynamic treatment in acid media under oxidative conditions. A noticeable increase in the capacitance for the functionalized carbon nanotubes mainly due to redox processes points out the formation of an electroactive polymer thin film on the CNTs surface along with covalently bonded functionalities. The CNTs functionalized using aminobenzoic acid rendered the highest capacitance values and surface nitrogen content, while the presence of sulfur and/or phosphorus groups in the aminobenzene structure yielded a lower functionalization degree. The oxygen reduction reaction (ORR) activity of the functionalized samples was similar to that of the parent CNTs, independently of the functional group present in the aminobenzene acid. Interestingly, a heat treatment in N2 atmosphere with a very low O2 concentration (3125 ppm) at 800 °C of the CNTs functionalized with aminobenzoic acid produced a material with high amounts of surface oxygen and nitrogen groups (12 and 4% at., respectively), that seem to modulate the electron-donor properties of the resulting material. The onset potential and limiting current for ORR was enhanced for this material. These are promising results that validates the use of electrochemistry for the synthesis of novel N-doped electrocatalysts for ORR in combination with adequate heat treatments.

Using multilevel modeling and mixed methods to make theoretical progress in microfoundations for strategy research

The microfoundations research agenda presents an expanded theoretical perspective because it considers individuals, their characteristics, and their interactions as relevant variables to help us understand firm-level strategic issues. However, microfoundations empirical research faces unique challenges because processes take place at different levels of analysis and these multilevel processes must be considered simultaneously. We describe multilevel modeling and mixed methods as methodological approaches whose use will allow for theoretical advancements. We describe key issues regarding the use of these two types of methods and, more importantly, discuss pressing substantive questions and topics that can be addressed with each of these methodological approaches with the goal of making theoretical advancements regarding the microfoundations research agenda and strategic management studies in general.

Successful functionalization of superporous zeolite templated carbon using aminobenzene acids and electrochemical methods

A novel and selective electrochemical functionalization of a highly reactive superporous zeolite templated carbon (ZTC) with two different aminobenzene acids (2-aminobenzoic and 4-aminobenzoic acid) was achieved. The functionalization was done through potentiodynamic treatment in acid media under oxidative conditions, which were optimized to preserve the unique ZTC structure. Interestingly, it was possible to avoid the electrochemical oxidation of the highly reactive ZTC structure by controlling the potential limit of the potentiodynamic experiment in presence of aminobenzene acids. The electrochemical characterization demonstrated the formation of polymer chains along with covalently bonded functionalities to the ZTC surface. The functionalized ZTCs showed several redox processes, producing a capacitance increase in both basic and acid media. The rate performance showed that the capacitance increase is retained at scan rates as high as 100 mV s−1, indicating that there is a fast charge transfer between the polymer chains formed inside the ZTC porosity or the new surface functionalities and the ZTC itself. The success of the proposed approach was also confirmed by using other characterization techniques, which confirmed the presence of different nitrogen groups in the ZTC surface. This promising method could be used to achieve highly selective functionalization of highly porous carbon materials.

Music and movement: A comparative study between the BAPNE and Suzuki Methods

The aim of this article is to compare the Suzuki and BAPNE methods based on bibliography published for both approaches. In the field of musical and instrumental education and especially for the childhood stage, the correct use of the body and voice are of fundamental importance. These two methods differ from one another; one principally musical and instrumental, which is the Suzuki method, and one non-musical, the BAPNE method, which aims at stimulating attention, concentration, memory and the executing function of the pupil through music and body percussion. Comparing different approaches may provide teachers with a useful insight for facing different issues related to their discipline.

Automatic extraction of syntactic semantic patterns for multilingual resources

In this paper we present an automatic system for the extraction of syntactic semantic patterns applied to the development of multilingual processing tools. In order to achieve optimum methods for the automatic treatment of more than one language, we propose the use of syntactic semantic patterns. These patterns are formed by a verbal head and the main arguments, and they are aligned among languages. In this paper we present an automatic system for the extraction and alignment of syntactic semantic patterns from two manually annotated corpora, and evaluate the main linguistic problems that we must deal with in the alignment process.

Real-time 3D semi-local surface patch extraction using GPGPU

Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

Thermogravimetry and Py–GC/MS techniques as fast qualitative methods for comparing the biochemical composition of Nannochloropsis oculata samples obtained under different culture conditions

Microalgae have many applications, such as biodiesel production or food supplement. Depending on the application, the optimization of certain fractions of the biochemical composition (proteins, carbohydrates and lipids) is required. Therefore, samples obtained in different culture conditions must be analyzed in order to compare the content of such fractions. Nevertheless, traditional methods necessitate lengthy analytical procedures with prolonged sample turn-around times. Results of the biochemical composition of Nannochloropsis oculata samples with different protein, carbohydrate and lipid contents obtained by conventional analytical methods have been compared to those obtained by thermogravimetry (TGA) and a Pyroprobe device connected to a gas chromatograph with mass spectrometer detector (Py–GC/MS), showing a clear correlation. These results suggest a potential applicability of these techniques as fast and easy methods to qualitatively compare the biochemical composition of microalgal samples.

Marine debris occurrence and treatment: A review

Marine debris produces a wide variety of negative environmental, economic, safety, health and cultural impacts. Most marine litter has a very low decomposition rate (as plastics, which are the most abundant type of marine debris), leading to a gradual, but significant accumulation in the coastal and marine environment. Along that time, marine debris is a significant source of chemical contaminants to the marine environment. Once extracted from the water, incineration is the method most widely used to treat marine debris. Other treatment methods have been tested, but they still need some improvement and so far have only been used in some countries. Several extraction and collection programs have been carried out. However, as marine debris keep entering the sea, these programs result insufficient and the problem of marine debris will continue its increase. The present work addresses the environmental impact and social aspects of the marine debris, with a review of the state of the art in the treatments of this kind of waste, together with an estimation of the worldwide occurrence and characteristics.