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Diego Cheda, Daniel Ponsa, & Antonio Lopez. (2012). Pedestrian Candidates Generation using Monocular Cues. In IEEE Intelligent Vehicles Symposium (pp. 7–12). IEEE Xplore.
Abstract: Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached.
Keywords: pedestrian detection
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Javier Vazquez, J. Kevin O'Regan, Maria Vanrell, & Graham D. Finlayson. (2012). A new spectrally sharpened basis to predict colour naming, unique hues, and hue cancellation. VSS - Journal of Vision, 12(6 (7)), 1–14.
Abstract: When light is reflected off a surface, there is a linear relation between the three human photoreceptor responses to the incoming light and the three photoreceptor responses to the reflected light. Different colored surfaces have different linear relations. Recently, Philipona and O'Regan (2006) showed that when this relation is singular in a mathematical sense, then the surface is perceived as having a highly nameable color. Furthermore, white light reflected by that surface is perceived as corresponding precisely to one of the four psychophysically measured unique hues. However, Philipona and O'Regan's approach seems unrelated to classical psychophysical models of color constancy. In this paper we make this link. We begin by transforming cone sensors to spectrally sharpened counterparts. In sharp color space, illumination change can be modeled by simple von Kries type scalings of response values within each of the spectrally sharpened response channels. In this space, Philipona and O'Regan's linear relation is captured by a simple Land-type color designator defined by dividing reflected light by incident light. This link between Philipona and O'Regan's theory and Land's notion of color designator gives the model biological plausibility. We then show that Philipona and O'Regan's singular surfaces are surfaces which are very close to activating only one or only two of such newly defined spectrally sharpened sensors, instead of the usual three. Closeness to zero is quantified in a new simplified measure of singularity which is also shown to relate to the chromaticness of colors. As in Philipona and O'Regan's original work, our new theory accounts for a large variety of psychophysical color data.
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Albert Clapes, Miguel Reyes, & Sergio Escalera. (2012). User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis. In 7th Conference on Articulated Motion and Deformable Objects (Vol. 7378, pp. 1–11). LNCS. Springer Berlin Heidelberg.
Abstract: We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.
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Jose Manuel Alvarez, Felipe Lumbreras, Antonio Lopez, & Theo Gevers. (2012). Understanding Road Scenes using Visual Cues.
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Sergio Vera, Debora Gil, Antonio Lopez, & Miguel Angel Gonzalez Ballester. (2012). Multilocal Creaseness Measure. IJ - The Insight Journal.
Abstract: This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.
Keywords: Ridges, Valley, Creaseness, Structure Tensor, Skeleton,
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Michal Drozdzal, Petia Radeva, Santiago Segui, Laura Igual, Carolina Malagelada, Fernando Azpiroz, et al. (2012). System and Method for Improving a Discriminative Model.
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Francesc Tanarro Marquez, Pau Gratacos Marti, F. Javier Sanchez, Joan Ramon Jimenez Minguell, Coen Antens, & Enric Sala i Esteva. (2012). A device for monitoring condition of a railway supply. European Patent Office.
Abstract: of a railway supply line when the supply line is in contact with a head of a pantograph of a vehicle in order to power said vehicle . The device includes a camera ( for monitoring parameters indicative of operating capability of said supply line.
The device is intended to monitor condition
tive of operating capability of said supply line. The device includes a reflective element. comprising a pattern , intended to be arranged onto the pantograph head . The camera is intended to be arranged on the vehicle (10) so as to register the pattern position regarding a vertical direction.
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Albert Andaluz. (2012). Harmonic Phase Flow: User's guide. Barcelona: CVC.
Abstract: HPF is a plugin for the computation of clinical scores under Osirix.
This manual provides a basic guide for experienced clinical staff. Chapter 1 provides the theoretical background in which this plugin is based.
Next, in chapter 2 we provide basic instructions for installing and uninstalling this plugin. chapter 3we shows a step-by-step scenario to compute clinical scores from tagged-MRI images with HPF. Finally, in chapter 4 we provide a quick guide for plugin developers
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Albert Andaluz, Francesc Carreras, Cristina Santa Marta, & Debora Gil. (2012). Myocardial torsion estimation with Tagged-MRI in the OsiriX platform. In Wiro Niessen(Erasmus MC) and Marc Modat(UCL) (Ed.), ISBI Workshop on Open Source Medical Image Analysis software. IEEE.
Abstract: Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es
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Sergio Escalera, Josep Moya, Laura Igual, Veronica Violant, & Maria Teresa Anguera. (2012). Automatic Human Behavior Analysis in ADHD. In Eunethydis 2nd International ADHD Conference.
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Lluis Gomez. (2012). Perceptual Organization for Text Extraction in Natural Scenes (Vol. 173). Master's thesis, , .
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Wenjuan Gong, Jordi Gonzalez, & Xavier Roca. (2012). Human Action Recognition based on Estimated Weak Poses. EURASIPJ - EURASIP Journal on Advances in Signal Processing, .
Abstract: We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.
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Fernando Barrera, Felipe Lumbreras, Cristhian Aguilera, & Angel Sappa. (2012). Planar-Based Multispectral Stereo. In 11th Quantitative InfraRed Thermography.
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Cristhian Aguilera, Fernando Barrera, Angel Sappa, & Ricardo Toledo. (2012). A Novel SIFT-Like-Based Approach for FIR-VS Images Registration. In 11th Quantitative InfraRed Thermography.
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German Ros, Angel Sappa, Daniel Ponsa, & Antonio Lopez. (2012). Visual SLAM for Driverless Cars: A Brief Survey. In IEEE Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles.
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