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Author |
Jose Manuel Alvarez; Theo Gevers; Y. LeCun; Antonio Lopez |
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Title |
Road Scene Segmentation from a Single Image |
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Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision |
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Volume |
7578 |
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VII |
Pages |
376-389 |
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Keywords |
road detection |
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Abstract |
Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes provides relevant contextual information to improve their understanding.
In this paper, we use a convolutional neural network based algorithm to learn features from noisy labels to recover the 3D scene layout of a road image. The novelty of the algorithm relies on generating training labels by applying an algorithm trained on a general image dataset to classify on–board images. Further, we propose a novel texture descriptor based on a learned color plane fusion to obtain maximal uniformity in road areas. Finally, acquired (off–line) and current (on–line) information are combined to detect road areas in single images.
From quantitative and qualitative experiments, conducted on publicly available datasets, it is concluded that convolutional neural networks are suitable for learning 3D scene layout from noisy labels and provides a relative improvement of 7% compared to the baseline. Furthermore, combining color planes provides a statistical description of road areas that exhibits maximal uniformity and provides a relative improvement of 8% compared to the baseline. Finally, the improvement is even bigger when acquired and current information from a single image are combined |
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Florence, Italy |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-33785-7 |
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ECCV |
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Admin @ si @ AGL2012; ADAS @ adas @ agl2012a |
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2022 |
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Author |
Susana Alvarez |
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Title |
Revisión de la teoría de los Textons Enfoque computacional en color |
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Book Whole |
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2012 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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El color y la textura son dos estímulos visuales importantes para la interpretación de las imágenes. La definición de descriptores computacionales que combinan estas dos características es aún un problema abierto. La dificultad se deriva esencialmente de la propia naturaleza de ambas, mientras que la textura es una propiedad de una región, el color es una propiedad de un punto.
Hasta ahora se han utilizado tres los tipos de aproximaciones para la combinación, (a) se describe la textura directamente en cada uno de los canales color, (b) se describen textura y color por separado y se combinan al final, y (c) la combinación se realiza con técnicas de aprendizaje automático. Considerando que este problema se resuelve en el sistema visual humano en niveles muy tempranos, en esta tesis se propone estudiar el problema a partir de la implementación directa de una teoría perceptual, la teoría de los textons, y explorar así su extensión a color.
Puesto que la teoría de los textons se basa en la descripción de la textura a partir de las densidades de los atributos locales, esto se adapta perfectamente al marco de trabajo de los descriptores holísticos (bag-of-words). Se han estudiado diversos descriptores basados en diferentes espacios de textons, y diferentes representaciones de las imágenes. Asimismo se ha estudiado la viabilidad de estos descriptores en una representación conceptual de nivel intermedio.
Los descriptores propuestos han demostrado ser muy eficientes en aplicaciones de recuperación y clasificación de imágenes, presentando ventajas en la generación de vocabularios. Los vocabularios se obtienen cuantificando directamente espacios de baja dimensión y la perceptualidad de estos espacios permite asociar semántica de bajo nivel a las palabras visuales. El estudio de los resultados permite concluir que si bien la aproximación holística es muy eficiente, la introducción de co-ocurrencia espacial de las propiedades de forma y color de los blobs de la imagen es un elemento clave para su combinación, hecho que no contradice las evidencias en percepción |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Maria Vanrell;Xavier Otazu |
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Alv2012b |
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2216 |
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Author |
Simone Balocco; Carlo Gatta; Marina Alberti; Xavier Carrillo; Juan Rigla; Petia Radeva |
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Title |
Relation between plaque type, plaque thickness, blood shear stress and plaque stress in coronary arteries assessed by X-ray Angiography and Intravascular Ultrasound |
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Journal Article |
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Year |
2012 |
Publication |
Medical Physics |
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MEDPHYS |
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39 |
Issue |
12 |
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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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MILAB |
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Admin @ si @BGA2012 |
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2170 |
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Author |
Nuria Cirera |
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Title |
Recognition of Handwritten Historical Documents |
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Report |
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2012 |
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CVC Technical Report |
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174 |
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Master's thesis |
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DAG |
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Admin @ si @ Cir2012 |
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2416 |
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Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados |
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Title |
Recherche de sous-graphes par encapsulation floue des cliques d'ordre 2: Application à la localisation de contenu dans les images de documents graphiques |
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Conference Article |
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2012 |
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Colloque International Francophone sur l'Écrit et le Document |
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149-162 |
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CIFED |
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DAG |
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Admin @ si @ LBR2012 |
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2382 |
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Author |
Xu Hu |
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Title |
Real-Time Part Based Models for Object Detection |
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Report |
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2012 |
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CVC Technical Report |
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171 |
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Admin @ si @ Hu2012 |
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2415 |
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Author |
Miguel Angel Bautista; Antonio Hernandez; Victor Ponce; Xavier Perez Sala; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera |
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Title |
Probability-based Dynamic TimeWarping for Gesture Recognition on RGB-D data |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis |
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Volume |
7854 |
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126-135 |
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Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost below a certain threshold is found within the test sequence. Nevertheless, either taking one single sample per gesture category or a set of isolated samples may not encode the variability of such gesture category. In this paper, a probability-based DTW for gesture recognition is proposed. Different samples of the same gesture pattern obtained from RGB-Depth data are used to build a Gaussian-based probabilistic model of the gesture. Finally, the cost of DTW has been adapted accordingly to the new model. The proposed approach is tested in a challenging scenario, showing better performance of the probability-based DTW in comparison to state-of-the-art approaches for gesture recognition on RGB-D data. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-40302-6 |
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WDIA |
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MILAB; OR;HuPBA;MV |
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no |
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Admin @ si @ BHP2012 |
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2120 |
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Author |
Naila Murray |
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Predicting Saliency and Aesthetics in Images: A Bottom-up Perspective |
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2012 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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In Part 1 of the thesis, we hypothesize that salient and non-salient image regions can be estimated to be the regions which are enhanced or assimilated in standard low-level color image representations. We prove this hypothesis by adapting a low-level model of color perception into a saliency estimation model. This model shares the three main steps found in many successful models for predicting attention in a scene: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. For such models, integrating spatial information and justifying the choice of various parameter values remain open problems. Our saliency model inherits a principled selection of parameters as well as an innate spatial pooling mechanism from the perception model on which it is based. This pooling mechanism has been fitted using psychophysical data acquired in color-luminance setting experiments. The proposed model outperforms the state-of-the-art at the task of predicting eye-fixations from two datasets. After demonstrating the effectiveness of our basic saliency model, we introduce an improved image representation, based on geometrical grouplets, that enhances complex low-level visual features such as corners and terminations, and suppresses relatively simpler features such as edges. With this improved image representation, the performance of our saliency model in predicting eye-fixations increases for both datasets.
In Part 2 of the thesis, we investigate the problem of aesthetic visual analysis. While a great deal of research has been conducted on hand-crafting image descriptors for aesthetics, little attention so far has been dedicated to the collection, annotation and distribution of ground truth data. Because image aesthetics is complex and subjective, existing datasets, which have few images and few annotations, have significant limitations. To address these limitations, we have introduced a new large-scale database for conducting Aesthetic Visual Analysis, which we call AVA. AVA contains more than 250,000 images, along with a rich variety of annotations. We investigate how the wealth of data in AVA can be used to tackle the challenge of understanding and assessing visual aesthetics by looking into several problems relevant for aesthetic analysis. We demonstrate that by leveraging the data in AVA, and using generic low-level features such as SIFT and color histograms, we can exceed state-of-the-art performance in aesthetic quality prediction tasks.
Finally, we entertain the hypothesis that low-level visual information in our saliency model can also be used to predict visual aesthetics by capturing local image characteristics such as feature contrast, grouping and isolation, characteristics thought to be related to universal aesthetic laws. We use the weighted center-surround responses that form the basis of our saliency model to create a feature vector that describes aesthetics. We also introduce a novel color space for fine-grained color representation. We then demonstrate that the resultant features achieve state-of-the-art performance on aesthetic quality classification.
As such, a promising contribution of this thesis is to show that several vision experiences – low-level color perception, visual saliency and visual aesthetics estimation – may be successfully modeled using a unified framework. This suggests a similar architecture in area V1 for both color perception and saliency and adds evidence to the hypothesis that visual aesthetics appreciation is driven in part by low-level cues. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Xavier Otazu;Maria Vanrell |
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Admin @ si @ Mur2012 |
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2212 |
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Author |
Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
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Title |
Predicting categorical colour perception in successive colour constancy |
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2012 |
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Perception |
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PER |
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41 |
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138 |
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Colour constancy is a perceptual mechanism that seeks to keep the colour of objects relatively stable under an illumination shift. Experiments haveshown that its effects depend on the number of colours present in the scene. We
studied categorical colour changes under different adaptation states, in particular, whether the colour categories seen under a chromatically neutral illuminant are the same after a shift in the chromaticity of the illumination. To do this, we developed the chromatic setting paradigm (2011 Journal of Vision11 349), which is as an extension of achromatic setting to colour categories. The paradigm exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. Our experiments were run on a CRT monitor (inside a dark room) under various simulated illuminants and restricting the number of colours of the Mondrian background to three, thus weakening the adaptation effect. Our results show a change in the colour categories present before (under neutral illumination) and after adaptation (under coloured illuminants) with a tendency for adapted colours to be less saturated than before adaptation. This behaviour was predicted by a simple
affine matrix model, adjusted to the chromatic setting results. |
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0301-0066 |
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Admin @ si @ RPV2012 |
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2188 |
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Karel Paleček; David Geronimo; Frederic Lerasle |
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Pre-attention cues for person detection |
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Conference Article |
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2012 |
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Cognitive Behavioural Systems, COST 2102 International Training School |
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Current state-of-the-art person detectors have been proven reliable and achieve very good detection rates. However, the performance is often far from real time, which limits their use to low resolution images only. In this paper, we deal with candidate window generation problem for person detection, i.e. we want to reduce the computational complexity of a person detector by reducing the number of regions that has to be evaluated. We base our work on Alexe’s paper [1], which introduced several pre-attention cues for generic object detection. We evaluate these cues in the context of person detection and show that their performance degrades rapidly for scenes containing multiple objects of interest such as pictures from urban environment. We extend this set by new cues, which better suits our class-specific task. The cues are designed to be simple and efficient, so that they can be used in the pre-attention phase of a more complex sliding window based person detector. |
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Dresden, Germany |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-34583-8 |
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COST-TS |
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ADAS |
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Admin @ si @ PGL2012 |
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2148 |
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Author |
Miguel Reyes; Albert Clapes; Luis Felipe Mejia; Jose Ramirez; Juan R Revilla; Sergio Escalera |
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Posture Analysis and Range of Movement Estimation using Depth Maps |
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Conference Article |
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2012 |
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21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis |
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7854 |
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97-105 |
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World Health Organization estimates that 80% of the world population is affected of back pain during his life. Current practices to analyze back problems are expensive, subjective, and invasive. In this work, we propose a novel tool for posture and range of movement estimation based on the analysis of 3D information from depth maps. Given a set of keypoints defined by the user, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matching using a novel point-to-point fitting procedure, and accurate measurements about posture, spinal curvature, and range of movement are computed. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent musculoskeletal disorders, such as back pain, as well as tracking the posture evolution of patients in rehabilitation treatments. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-40302-6 |
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WDIA |
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HuPBA;MILAB |
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no |
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Admin @ si @ RCM2012 |
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2121 |
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Bogdan Raducanu; Fadi Dornaika |
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Pose-Invariant Face Recognition in Videos for Human-Machine Interaction |
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Conference Article |
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2012 |
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12th European Conference on Computer Vision |
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7584 |
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566.575 |
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Human-machine interaction is a hot topic nowadays in the communities of computer vision and robotics. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, pose, and occlusions. In this paper, we propose a novel approach for robust pose-invariant face recognition for human-robot interaction based on the real-time fitting of a 3D deformable model to input images taken from video sequences. More concrete, our approach generates a rectified face image irrespective with the actual head-pose orientation. Experimental results performed on Honda video database, using several manifold learning techniques, show a distinct advantage of the proposed method over the standard 2D appearance-based snapshot approach. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-33867-0 |
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ECCVW |
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OR;MV |
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Admin @ si @ RaD2012e |
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2182 |
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Author |
Jorge Bernal |
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Title |
Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps |
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2012 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. Our contribution, in the field of intelligent systems for colonoscopy, aims at providing a polyp localization and a polyp segmentation system based on a model of appearance for polyps. To develop both methods we define a model of appearance for polyps, which describes a polyp as enclosed by intensity valleys. The novelty of our contribution resides on the fact that we include in our model aspects of the image formation and we also consider the presence of other elements from the endoluminal scene such as specular highlights and blood vessels, which have an impact on the performance of our methods. In order to develop our polyp localization method we accumulate valley information in order to generate energy maps, which are also used to guide the polyp segmentation. Our methods achieve promising results in polyp localization and segmentation. As we want to explore the usability of our methods we present a comparative analysis between physicians fixations obtained via an eye tracking device and our polyp localization method. The results show that our method is indistinguishable to novice physicians although it is far from expert physicians. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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F. Javier Sanchez;Fernando Vilariño |
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800 |
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MV |
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no |
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Admin @ si @ Ber2012 |
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2211 |
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Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
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Title |
Planar-Based Multispectral Stereo |
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Conference Article |
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2012 |
Publication |
11th Quantitative InfraRed Thermography |
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Naples, Italy |
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QIRT |
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ADAS |
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no |
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Admin @ si @ BLA2012 |
Serial |
2016 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Photometric Invariance by Machine Learning |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Color in Computer Vision: Fundamentals and Applications |
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Volume |
7 |
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Pages |
113-134 |
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Keywords |
road detection |
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Publisher |
iConcept Press Ltd |
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Editor |
Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek |
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978-0-470-89084-4 |
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ADAS |
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no |
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Call Number |
Admin @ si @ AlL2012 |
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2186 |
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