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| Author | R. de Nijs; Sebastian Ramos; Gemma Roig; Xavier Boix; Luc Van Gool; K. Kühnlenz. | ||||
| Title | On-line Semantic Perception Using Uncertainty | Type | Conference Article | ||
| Year | 2012 | Publication | International Conference on Intelligent Robots and Systems | Abbreviated Journal | IROS |
| Volume | Issue | Pages  |
4185-4191 | ||
| Keywords | Semantic Segmentation | ||||
| Abstract | Visual perception capabilities are still highly unreliable in unconstrained settings, and solutions might not beaccurate in all regions of an image. Awareness of the uncertainty of perception is a fundamental requirement for proper high level decision making in a robotic system. Yet, the uncertainty measure is often sacrificed to account for dependencies between object/region classifiers. This is the case of Conditional Random Fields (CRFs), the success of which stems from their ability to infer the most likely world configuration, but they do not directly allow to estimate the uncertainty of the solution. In this paper, we consider the setting of assigning semantic labels to the pixels of an image sequence. Instead of using a CRF, we employ a Perturb-and-MAP Random Field, a recently introduced probabilistic model that allows performing fast approximate sampling from its probability density function. This allows to effectively compute the uncertainty of the solution, indicating the reliability of the most likely labeling in each region of the image. We report results on the CamVid dataset, a standard benchmark for semantic labeling of urban image sequences. In our experiments, we show the benefits of exploiting the uncertainty by putting more computational effort on the regions of the image that are less reliable, and use more efficient techniques for other regions, showing little decrease of performance | ||||
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| Area | Expedition | Conference | IROS | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ NRR2012 | Serial | 2378 | ||
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| Author | Susana Alvarez; Maria Vanrell | ||||
| Title | Texton theory revisited: a bag-of-words approach to combine textons | Type | Journal Article | ||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 45 | Issue | 12 | Pages |
4312-4325 |
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| Abstract | The aim of this paper is to revisit an old theory of texture perception and
update its computational implementation by extending it to colour. With this in mind we try to capture the optimality of perceptual systems. This is achieved in the proposed approach by sharing well-known early stages of the visual processes and extracting low-dimensional features that perfectly encode adequate properties for a large variety of textures without needing further learning stages. We propose several descriptors in a bag-of-words framework that are derived from different quantisation models on to the feature spaces. Our perceptual features are directly given by the shape and colour attributes of image blobs, which are the textons. In this way we avoid learning visual words and directly build the vocabularies on these lowdimensionaltexton spaces. Main differences between proposed descriptors rely on how co-occurrence of blob attributes is represented in the vocabularies. Our approach overcomes current state-of-art in colour texture description which is proved in several experiments on large texture datasets. |
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| ISSN | 0031-3203 | ISBN | Medium | ||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ AlV2012a | Serial | 2130 | ||
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| Author | Simone Balocco; Carlo Gatta; Marina Alberti; Xavier Carrillo; Juan Rigla; Petia Radeva | ||||
| Title | Relation between plaque type, plaque thickness, blood shear stress and plaque stress in coronary arteries assessed by X-ray Angiography and Intravascular Ultrasound | Type | Journal Article | ||
| Year | 2012 | Publication | Medical Physics | Abbreviated Journal | MEDPHYS |
| Volume | 39 | Issue | 12 | Pages |
7430-7445 |
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| Abstract | PMID 23231293
PURPOSE: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries. METHODS: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations. RESULTS: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall. CONCLUSIONS: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. |
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @BGA2012 | Serial | 2170 | ||
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| Author | Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo | ||||
| Title | Multispectral Image Feature Points | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 9 | Pages |
12661-12672 |
| Keywords | multispectral image descriptor; color and infrared images; feature point descriptor | ||||
| Abstract | Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ ABL2012 | Serial | 2154 | ||
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| Author | Cesar Isaza; Joaquin Salas; Bogdan Raducanu | ||||
| Title | Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 10 | Pages |
13333-13348 |
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| Abstract | In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection. | ||||
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ ISR2012b | Serial | 2173 | ||
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| Author | Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera | ||||
| Title | GrabCut-Based Human Segmentation in Video Sequences | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 11 | Pages |
15376-15393 |
| Keywords | segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field | ||||
| Abstract | In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ HRP2012 | Serial | 2147 | ||
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| Author | Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta | ||||
| Title | On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
| Volume | 26 | Issue | 5 | Pages |
1263002-126027 |
| Keywords | Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025 | ||||
| Abstract | 0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images. |
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ LRF2012 | Serial | 2128 | ||
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