http://hdl.handle.net/2117/225 2013-06-19T10:16:00Z http://hdl.handle.net/2117/19520 Title: Towards a format-agnostic approach for production, delivery and rendering of immersive media Authors: Niamut, O.A.; Kaiser, R.; Kienast, G.; Kochale, A.; Spille, J.; Schreer, Oliver; Ruiz Hidalgo, Javier; Macq, J.; Shirley, Ben Abstract: The media industry is currently being pulled in the often-opposing directions of increased realism (high resolution, stereoscopic, large screen) and personalization (selection and control of content, availability on many devices). We investigate the feasibility of an end-to-end format-agnostic approach to support both these trends. In this paper, different aspects of a format- agnostic capture, production, delivery and rendering system are discussed. At the capture stage, the concept of layered scene representation is introduced, including panoramic video and 3D audio capture. At the analysis stage, a virtual director component is discussed that allows for automatic execution of cinematographic principles, using feature tracking and saliency detection. At the delivery stage, resolution-independent audiovisual transport mechanisms for both managed and unmanaged networks are treated. In the rendering stage, a rendering process that includes the manipulation of audiovisual content to match the connected display and loudspeaker properties is introduced. Different parts of the complete system are revisited demonstrating the requirements and the potential of this advanced concept. 2013-06-05T17:34:40Z http://hdl.handle.net/2117/19490 Title: Work in progress - Cooperative and competitive projects for engaging students in advanced ICT subjects Authors: Pardàs Feliu, Montse; Bonafonte Cávez, Antonio Abstract: In this paper we present a specific kind of projects that can be used for project-based learning in engineering subjects. The subjects must combine lectures with projects, in order to provide the technical competences together with additional skills such as teamwork learning, oral and written communication skills and application of theory to practice. The projects proposed consist on improving an elemental baseline system. The system is decomposed in modules that correspond to the topics that have been learnt during the lectures. For improving the system, the class is divided in groups and each group has to propose, implement, assess and report a better system. In order to be able to improve the system with a limited amount of time and effort the students need to make a coherent proposal and split the project in several tasks that are usually developed by one or two students. The students within a group cooperate to achieve a better system, but groups compete for the best results. We have already implemented this kind of project in a Speech Processing course and we plan to apply it in a Video Coding course. 2013-06-03T18:32:45Z http://hdl.handle.net/2117/19460 Title: Multimedia copyright protection platform demonstrator Authors: Soriano Ibáñez, Miguel; Fernández Muñoz, Marcel; Sayrol Clols, Elisa; Tomás Buliart, Joan; Casanellas, Joan; Pegueroles Vallés, Josep R.; Hernández Serrano, Juan Abstract: The work presented in this paper consists in the development of a portable platform to protect the copyright and distribution rights of digital contents, and empirically demonstrate the capacity of several marking and tracing algorithms. This platform is used to verify, at a practical level, the strength properties of digital watermarking and fingerprinting marks. Initially, two watermarking algorithms, one based on spread-spectrum techniques and the other based on QIM (Quantization Index Modulation), have been implemented. Moreover, we use these watermarking algorithms to embed a fingerprinting code, based on code concatenation, equipped with an efficient tracing algorithm. In this paper we focus on the implementation issues of the Java-based platform, that consists of three main packages that are fully described 2013-05-30T13:22:18Z http://hdl.handle.net/2117/19419 Title: Hyperspectral image representation and processing with binary partition trees Authors: Valero Valbuena, Silvia; Salembier Clairon, Philippe Jean; Chanussot, Jocelyn Abstract: The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image-processing tools. This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the binary partition tree (BPT). This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure. Hence, the BPT succeeds in presenting: 1) the decomposition of the image in terms of coherent regions, and 2) the inclusion relations of the regions in the scene. Based on region-merging techniques, the BPT construction is investigated by studying the hyperspectral region models and the associated similarity metrics. Once the BPT is constructed, the fixed tree structure allows implementing efficient and advanced application-dependent techniques on it. The application-dependent processing of BPT is generally implemented through a specific pruning of the tree. In this paper, a pruning strategy is proposed and discussed in a classification context. Experimental results on various hyperspectral data sets demonstrate the interest and the good performances of the BPT representation. 2013-05-27T17:50:52Z http://hdl.handle.net/2117/19368 Title: Full high-dynamic range images for dynamic scenes Authors: Ramírez Orozco, Raissel; Martín, Ignacio; Loscos, Céline; Vázquez Alcocer, Pere Pau Abstract: The limited dynamic range of digital images can be extended by composing photographs of the same scene taken with the same camera at the same view point at di erent exposure times. This is a standard procedure for static scenes but a challenging task for dynamic ones. Several methods have been presented but few recover high dynamic range within moving areas. We present a method to recover full high dynamic range (HDR) images from dynamic scenes, even in moving regions. Our method has 3 steps. Firstly, areas a ected by motion are detected to generate a ghost mask. Secondly, we register dynamic objects over a reference image (the best exposed image in the input sequence). Thirdly, we combine the registered input photographs to recover HDR values in a whole image using a weighted average function. Once matching is found, the assembling step guarantees that all aligned pixels will contribute to the nal result, including dynamic content. Tests were made on more than 20 sets of sequences, with moving cars or pedestrians and di erent background. Our results show that Image Mapping Function approach detects best motion regions while Normalized Cross Correlation o ers the best deal speed-accuracy for image registration. Results from our method o ers better result when moving object are roughly rigid and their movement is mostly rigid. The nal composition is an HDR image with no ghosting and all dynamic content present in HDR values. 2013-05-22T08:40:29Z http://hdl.handle.net/2117/19316 Title: Region-based filtering of images and video sequences: a morphological viewpoint Authors: Salembier Clairon, Philippe Jean 2013-05-16T14:39:40Z http://hdl.handle.net/2117/19261 Title: Depth estimation of frames in image sequences using motion occlusions Authors: Palou Visa, Guillem; Salembier Clairon, Philippe Jean Abstract: This paper proposes a system to depth order regions of a frame belonging to a monocular image sequence. For a given frame, re- gions are ordered according to their relative depth using the previous and following frames. The algorithm estimates occluded and disoccluded pixels belonging to the central frame. Afterwards, a Binary Partition Tree (BPT) is constructed to obtain a hierarchical, region based repre- sentation of the image. The nal depth partition is obtained by means of energy minimization on the BPT. To achieve a global depth ordering from local occlusion cues, a depth order graph is constructed and used to eliminate contradictory local cues. Results of the system are evaluated and compared with state of the art gure/ground labeling systems on several datasets, showing promising results. 2013-05-15T15:11:26Z http://hdl.handle.net/2117/19152 Title: Los niveles de determinación como herramienta para analizar tareas de modelización matemática Authors: Gómez Urgellés, Joan Vicenç Abstract: Este trabajo se enmarca en las nuevas necesidades y expectativas de la educación matemática en el sistema educativo español: "preparar al alumno para su incorporación a estudios superiores y para su inserción laboral, y formado para el ejercicio de sus derechos y obligaciones en la vida como ciudadanas y ciudadanos" 2013-05-09T14:08:10Z http://hdl.handle.net/2117/18907 Title: Intoxicació tecnològica: De l'adicció a la seducció Authors: Gómez Urgellés, Joan Vicenç 2013-04-19T17:59:28Z http://hdl.handle.net/2117/18885 Title: Modelling in spanish secondary education: description of a practical experience Authors: Gómez Urgellés, Joan Vicenç Abstract: The objective of this work is to present preliminary results of a study about the situation of modelling in Spanish secondary education and a proposal of action. Within the framework of anthropological theory we will show, through the analysis of the official syllabus, that modelling is knowledge to be taught. Despite this, after an analysis of official texts, we have observed that didactic formation of secondary teachers is very poor. Through an experience, developed and implemented in classroom by one of the authors, we will show a different way to work modelling tasks in secondary education. 2013-04-18T18:33:18Z http://hdl.handle.net/2117/18542 Title: Can our TV robustly understand human gestures? Real-Time Gesture Localization in Range Data Authors: López Méndez, Adolfo; Casas Pla, Josep Ramon Abstract: The 'old' remote falls short of requirements when confronted with digital convergence for living room displays. Enriched options to watch, manage and interact with content on large displays demand improved means of interaction. Concurrently, gesture recognition is increasingly present in human-computer interaction for gaming applications. In this paper we propose a gesture localization framework for interactive display of audio-visual content. The proposed framework works with range data captured from a single consumer depth camera. We focus on still gestures because they are generally user friendly (users do not have to make complex and tiring movements) and allow formulating the problem in terms of object localization. Our method is based on random forests, which have shown an excellent performance on classification and regression tasks. In this work, however, we aim at a specific class of localization problems involving highly unbalanced data: positive examples appear during a small fraction of space and time. We study the impact of this natural unbalance on the random forest learning and we propose a framework to robustly detect gestures on range images in real applications. Our experiments with offline data show the effectiveness of our approach. We also present a real-time application where users can control the TV display with a reduced set of still gestures. 2013-04-02T12:43:38Z http://hdl.handle.net/2117/18496 Title: Metric learning from poses for temporal clustering of human motion Authors: López Méndez, Adolfo; Gall, Juergen; Casas Pla, Josep Ramon; van Gool, Luc Abstract: Temporal clustering of human motion into semantically meaningful behaviors is a challenging task. While unsupervised methods do well to some extent, the obtained clusters often lack a semantic interpretation. In this paper, we propose to learn what makes a sequence of human poses different from others such that it should be annotated as an action. To this end, we formulate the problem as weakly supervised temporal clustering for an unknown number of clusters. Weak supervision is attained by learning a metric from the implicit semantic distances derived from already annotated databases. Such a metric contains some low-level semantic information that can be used to effectively segment a human motion sequence into distinct actions or behaviors. The main advantage of our approach is that metrics can be successfully used across datasets, making our method a compelling alternative to unsupervised methods. Experiments on publicly available mocap datasets show the effectiveness of our approach. 2013-03-22T13:04:35Z http://hdl.handle.net/2117/18450 Title: Foreground objects segmentation for moving camera scenarios based on SCGMM Authors: Gallego, Jaime; Pardàs Feliu, Montse; Solano, Montse Abstract: In this paper we present a new system for segmenting non-rigid objects in moving camera sequences for indoor and outdoor sce narios that achieves a correct object segmentation via global MAP-MRF framework formulation for the foreground and background classification task. Our proposal, suitable for video indexation applications, receives as an input an initial segmentation of the object to segment and it consists of two region-based parametric probabilistic models to model the spatial (x,y) and color (r,g,b) domains of the foreground and background classes. Both classes rival each other in modeling the regions that appear within a dynamic region of interest that includes the foreground object to segment and also, the background regions that surrounds the object. The results presented in the paper show the correctness of the object segmentation, reducing false positive and false negative detections originated by the new background regions that appear near the region of the object 2013-03-21T10:45:10Z http://hdl.handle.net/2117/18425 Title: Gene expression data classification combining hierarchical representation and efficient feature selection Authors: Bosio, Mattia; Bellot Pujalte, Pau; Salembier Clairon, Philippe Jean; Oliveras Vergés, Albert Abstract: A general framework for microarray data classification is proposed in this paper. It pro- duces precise and reliable classifiers through a two-step approach. At first, the original feature set is enhanced by a new set of features called metagenes. These new features are obtained through a hierarchical clustering process on the original data. Two different metagene generation rules have been analyzed, called Treelets clustering and Euclidean clustering. Metagenes creation is attractive for several reasons: first, they can improve the classification since they broaden the available feature space and capture the com- mon behavior of similar genes reducing the residual measurement noise. Furthermore, by analyzing some of the chosen metagenes for classification with gene set enrichment analysis algorithms, it is shown how metagenes can summarize the behavior of func- tionally related probe sets. Additionally, metagenes can point out, still undocumented, highly discriminant probe sets numerically related to other probes endowed with prior biological information in order to contribute to the knowledge discovery process. The second step of the framework is the feature selection which applies the Improved Sequential Floating Forward Selection algorithm (IFFS) to properly choose a subset from the available feature set for classification composed of genes and metagenes. Considering the microarray sample scarcity problem, besides the classical error rate, a reliability measure is introduced to improve the feature selection process. Different scoring schemes are studied to choose the best one using both error rate and reliability. The Linear Discriminant Analysis classifier (LDA) has been used throughout this work, due to its good characteristics, but the proposed framework can be used with almost any classifier. The potential of the proposed framework has been evaluated analyzing all the publicly available datasets offered by the Micro Array Quality Control Study, phase II (MAQC). The comparative results showed that the proposed framework can compete with a wide variety of state of the art alternatives and it can obtain the best mean performance if a particular setup is chosen. A Monte Carlo simulation confirmed that the proposed framework obtains stable and repeatable results. 2013-03-19T18:10:53Z http://hdl.handle.net/2117/18356 Title: Depth ordering on image sequences using motion occlusions Authors: Palou Visa, Guillem; Salembier Clairon, Philippe Jean Abstract: This paper proposes a system to obtain the depth order of frames in image sequences using motion occlusion cues. The system first computes the forward and backward flows with the previous and next frames and estimates the occluded points. To obtain a region representation of the image, a Binary Partition Tree (BPT) is created for each frame. To estimate occlusion relations in the image, projective flow models are fitted to all regions in the image. The depth order solution is obtained by minimizing over the tree structure a cost function based on occlusion relations and the number of regions. Results show that optical flow algorithms can be used directly to estimate occlusion points. Promising results are obtained combining motion occlusions and region information by means of a BPT. Evaluation is performed comparing current state-of-the-art algorithms on figure/ground assignments, showing that the performance of the proposed system is comparable to current algorithms. 2013-03-15T16:02:14Z