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Mohammad Rouhani. (2009). 3D Data Fitting and Tracking for Real Time Applications (Vol. 138). Master's thesis, , .
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Partha Pratim Roy, Josep Llados, & Umapada Pal. (2009). A Complete System for Detection and Recognition of Text in Graphical Documents using Background Information. In 5th International Conference on Computer Vision Theory and Applications.
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Albert Gordo. (2009). A Cyclic Page Layout Descriptor for Document Classification & Retrieval (Vol. 128). Master's thesis, , Bellaterra, Barcelona.
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Nicola Bellotto, Eric Sommerlade, Ben Benfold, Charles Bibby, I. Reid, Daniel Roth, et al. (2009). A Distributed Camera System for Multi-Resolution Surveillance. In 3rd ACM/IEEE International Conference on Distributed Smart Cameras.
Abstract: We describe an architecture for a multi-camera, multi-resolution surveillance system. The aim is to support a set of distributed static and pan-tilt-zoom (PTZ) cameras and visual tracking algorithms, together with a central supervisor unit. Each camera (and possibly pan-tilt device) has a dedicated process and processor. Asynchronous interprocess communications and archiving of data are achieved in a simple and effective way via a central repository, implemented using an SQL database. Visual tracking data from static views are stored dynamically into tables in the database via client calls to the SQL server. A supervisor process running on the SQL server determines if active zoom cameras should be dispatched to observe a particular target, and this message is effected via writing demands into another database table. We show results from a real implementation of the system comprising one static camera overviewing the environment under consideration and a PTZ camera operating under closed-loop velocity control, which uses a fast and robust level-set-based region tracker. Experiments demonstrate the effectiveness of our approach and its feasibility to multi-camera systems for intelligent surveillance.
Keywords: 10.1109/ICDSC.2009.5289413
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Fadi Dornaika, & Angel Sappa. (2009). A Featureless and Stochastic Approach to On-board Stereo Vision System Pose. IMAVIS - Image and Vision Computing, 27(9), 1382–1393.
Abstract: This paper presents a direct and stochastic technique for real-time estimation of on-board stereo head’s position and orientation. Unlike existing works which rely on feature extraction either in the image domain or in 3D space, our proposed approach directly estimates the unknown parameters from the stream of stereo pairs’ brightness. The pose parameters are tracked using the particle filtering framework which implicitly enforces the smoothness constraints on the estimated parameters. The proposed technique can be used with a driver assistance applications as well as with augmented reality applications. Extended experiments on urban environments with different road geometries are presented. Comparisons with a 3D data-based approach are presented. Moreover, we provide a performance study aiming at evaluating the accuracy of the proposed approach.
Keywords: On-board stereo vision system; Pose estimation; Featureless approach; Particle filtering; Image warping
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Pierluigi Casale, Oriol Pujol, Petia Radeva, & Jordi Vitria. (2009). A First Approach to Activity Recognition Using Topic Models. In 12th International Conference of the Catalan Association for Artificial Intelligence (Vol. 202, pp. 74–82).
Abstract: In this work, we present a first approach to activity patterns discovery by mean of topic models. Using motion data collected with a wearable device we prototype, TheBadge, we analyse raw accelerometer data using Latent Dirichlet Allocation (LDA), a particular instantiation of topic models. Results show that for particular values of the parameters necessary for applying LDA to a countinous dataset, good accuracies in activity classification can be achieved.
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C. Alejandro Parraga, Javier Vazquez, & Maria Vanrell. (2009). A new cone activation-based natural images dataset. PER - Perception, 36, 180.
Abstract: We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website.
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Mohammad Rouhani, & Angel Sappa. (2009). A Novel Approach to Geometric Fitting of Implicit Quadrics. In 8th International Conference on Advanced Concepts for Intelligent Vision Systems (Vol. 5807, 121–132). LNCS. Springer Berlin Heidelberg.
Abstract: This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results.
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Mathieu Nicolas Delalandre, Jean-Yves Ramel, Ernest Valveny, & Muhammad Muzzamil Luqman. (2009). A Performance Characterization Algorithm for Symbol Localization. In 8th IAPR International Workshop on Graphics Recognition (pp. 3–11). Springer.
Abstract: In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
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Marçal Rusiñol, & Josep Llados. (2009). A Performance Evaluation Protocol for Symbol Spotting Systems in Terms of Recognition and Location Indices. IJDAR - International Journal on Document Analysis and Recognition, 12(2), 83–96.
Abstract: Symbol spotting systems are intended to retrieve regions of interest from a document image database where the queried symbol is likely to be found. They shall have the ability to recognize and locate graphical symbols in a single step. In this paper, we present a set of measures to evaluate the performance of a symbol spotting system in terms of recognition abilities, location accuracy and scalability. We show that the proposed measures allow to determine the weaknesses and strengths of different methods. In particular we have tested a symbol spotting method based on a set of four different off-the-shelf shape descriptors.
Keywords: Performance evaluation; Symbol Spotting; Graphics Recognition
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Miquel Ferrer, Dimosthenis Karatzas, Ernest Valveny, & Horst Bunke. (2009). A Recursive Embedding Approach to Median Graph Computation. In 7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition (Vol. 5534, 113–123). LNCS. Springer Berlin Heidelberg.
Abstract: The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches.
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Debora Gil, Jaume Garcia, Ruth Aris, Guillaume Houzeaux, & Manuel Vazquez. (2009). A Riemmanian approach to cardiac fiber architecture modelling. In R. L. R. V. L. Nithiarasu (Ed.), 1st International Conference on Mathematical & Computational Biomedical Engineering (pp. 59–62). Swansea (UK).
Abstract: There is general consensus that myocardial fiber architecture should be modelled in order to fully understand the electromechanical properties of the Left Ventricle (LV). Diffusion Tensor magnetic resonance Imaging (DTI) is the reference image modality for rapid measurement of fiber orientations by means of the tensor principal eigenvectors. In this work, we present a mathematical framework for across subject comparison of the local geometry of the LV anatomy including the fiber architecture from the statistical analysis of DTI studies. We use concepts of differential geometry for defining a parametric domain suitable for statistical analysis of a low number of samples. We use Riemannian metrics to define a consistent computation of DTI principal eigenvector modes of variation. Our framework has been applied to build an atlas of the LV fiber architecture from 7 DTI normal canine hearts.
Keywords: cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry.
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Albert Gordo, & Ernest Valveny. (2009). A rotation invariant page layout descriptor for document classification and retrieval. In 10th International Conference on Document Analysis and Recognition (481–485).
Abstract: Document classification usually requires of structural features such as the physical layout to obtain good accuracy rates on complex documents. This paper introduces a descriptor of the layout and a distance measure based on the cyclic dynamic time warping which can be computed in O(n2). This descriptor is translation invariant and can be easily modified to be scale and rotation invariant. Experiments with this descriptor and its rotation invariant modification are performed on the Girona archives database and compared against another common layout distance, the minimum weight edge cover. The experiments show that these methods outperform the MWEC both in accuracy and speed, particularly on rotated documents.
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Wenjuan Gong. (2009). Action priors for human pose tracking by particle filter. Master's thesis, , Bellaterra, Barcelona.
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Ignasi Rius, Jordi Gonzalez, Javier Varona, & Xavier Roca. (2009). Action-specific motion prior for efficient bayesian 3D human body tracking. PR - Pattern Recognition, 42(11), 2907–2921.
Abstract: In this paper, we aim to reconstruct the 3D motion parameters of a human body
model from the known 2D positions of a reduced set of joints in the image plane.
Towards this end, an action-specific motion model is trained from a database of real
motion-captured performances. The learnt motion model is used within a particle
filtering framework as a priori knowledge on human motion. First, our dynamic
model guides the particles according to similar situations previously learnt. Then, the solution space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, we are able to track the 3D configuration of the full human body from several cycles of walking motion sequences using only the 2D positions of a very reduced set of joints from lateral or frontal viewpoints.
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