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Nataliya Shapovalova. (2010). On Importance of Interaction and Context (Vol. 155). Master's thesis, , .
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Zhanwu Xiong. (2010). A Pompd Model for Active Camera Control (Vol. 156). Master's thesis, , .
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Olivier Penacchio, C. Alejandro Parraga, & Maria Vanrell. (2010). Natural Scene Statistics account for Human Cones Ratios. PER - Perception. ECVP Abstract Supplement, 39, 101.
Abstract: In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant di erences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the di erences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly di erent(more di use) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space.
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Bogdan Raducanu, & D. Gatica-Perez. (2012). Inferring competitive role patterns in reality TV show through nonverbal analysis. MTAP - Multimedia Tools and Applications, 56(1), 207–226.
Abstract: This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of “The Apprentice” reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority.
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Neus Salvatella, E Fernandez-Nofrerias, Francesco Ciompi, O. Rodriguez-Leor, H. Tizon, Xavier Carrillo, et al. (2010). Radial Artery Volume Changes After Administration Of Two Different Intra-arterial Drug Regimens. Assessment by Intravascular Ultrasound. JACC - Journal of the American College of Cardiology, 56(13s1), B119.
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Neus Salvatella, E Fernandez-Nofrerias, Francesco Ciompi, O. Rodriguez-Leor, Xavier Carrillo, R. Hemetsberger, et al. (2010). Canvis de volum a la arteria radial despres de la administracio de dos tractaments vasodilatadors. Avaluacio mitjançant ecografia intravascular. In 22nd Congres Societat Catalana de Cardiologia, (179).
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O. Rodriguez-Leor, R. Hemetsberger, Francesco Ciompi, E Fernandez-Nofrerias, Angel Serrano, M. Bernet, et al. (2010). Caracteritzacio automatica de la placa mitjançant analisis del espectre de radiofreqüencia en estudi de ecografia intracoronaria: resultat de la fusio de dades invivo i exvivo. In 22nd Congres Societat Catalana de Cardiologia, (131).
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Daniel Ponsa, Joan Serrat, & Antonio Lopez. (2011). On-board image-based vehicle detection and tracking. TIM - Transactions of the Institute of Measurement and Control, 33(7), 783–805.
Abstract: In this paper we present a computer vision system for daytime vehicle detection and localization, an essential step in the development of several types of advanced driver assistance systems. It has a reduced processing time and high accuracy thanks to the combination of vehicle detection with lane-markings estimation and temporal tracking of both vehicles and lane markings. Concerning vehicle detection, our main contribution is a frame scanning process that inspects images according to the geometry of image formation, and with an Adaboost-based detector that is robust to the variability in the different vehicle types (car, van, truck) and lighting conditions. In addition, we propose a new method to estimate the most likely three-dimensional locations of vehicles on the road ahead. With regards to the lane-markings estimation component, we have two main contributions. First, we employ a different image feature to the other commonly used edges: we use ridges, which are better suited to this problem. Second, we adapt RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane markings to the image features. We qualitatively assess our vehicle detection system in sequences captured on several road types and under very different lighting conditions. The processed videos are available on a web page associated with this paper. A quantitative evaluation of the system has shown quite accurate results (a low number of false positives and negatives) at a reasonable computation time.
Keywords: vehicle detection
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David Geronimo, & Antonio Lopez. (2010). Deteccion de Peatones para Sistemas Avanzados de Asistencia al Conductor.
Abstract: Los sistemas de asistencia al conductor, y particularmente los sistemas de protección de peatones, representan uno de los campos de investigación más activos dedicados a la mejora de la seguridad vial. El mayor desafío es el desarrollo de sistemas a bordo fiables de detección de peatones. En esta revisión del estado de la técnica de la detección de peatones, se divide el problema en diferentes etapas, cada una con responsabilidades propias dentro del sistema. Esta división facilita el posterior análisis y discusión de cada uno de los métodos en la literatura, favoreciendo la comparación entre ellos. Finalmente se discuten los temas más importantes de este campo poniendo especial énfasis en las necesidades actuales y los desafíos futuros.
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Joan Serrat, & Antonio Lopez. (2010). Deteccion automatica de lineas de carril para la asistencia a la conduccion.
Abstract: La detección por cámara de las líneas de carril en las carreteras puede ser una solución asequible a los riesgos de conducción generados por los adelantamientos o las salidas de carril. Este trabajo propone un sistema que funciona en tiempo real y que obtiene muy buenos resultados. El sistema está preparado para identificar las líneas en condiciones de visibilidad poco favorables, como puede ser la conducción nocturna o con otros vehículos que dificulten la visión.
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Xavier Otazu, C. Alejandro Parraga, & Maria Vanrell. (2010). Towards a unified chromatic inducction model. VSS - Journal of Vision, 10(12:5), 1–24.
Abstract: In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data.
Keywords: Visual system; Color induction; Wavelet transform
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Jose Manuel Alvarez, Theo Gevers, & Antonio Lopez. (2010). Learning photometric invariance for object detection. IJCV - International Journal of Computer Vision, 90(1), 45–61.
Abstract: Impact factor: 3.508 (the last available from JCR2009SCI). Position 4/103 in the category Computer Science, Artificial Intelligence. Quartile
Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, this approach may be too restricted to model real-world scenes in which different reflectance mechanisms can hold simultaneously.
Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is computed composed of both color variants and invariants. Then, the proposed method combines these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, our fusion method uses a multi-view approach to minimize the estimation error. In this way, the proposed method is robust to data uncertainty and produces properly diversified color invariant ensembles. Further, the proposed method is extended to deal with temporal data by predicting the evolution of observations over time.
Experiments are conducted on three different image datasets to validate the proposed method. Both the theoretical and experimental results show that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning, and outperforms state-of-the-art detection techniques in the field of object, skin and road recognition. Considering sequential data, the proposed method (extended to deal with future observations) outperforms the other methods
Keywords: road detection
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Sergio Escalera, Oriol Pujol, Eric Laciar, Jordi Vitria, Esther Pueyo, & Petia Radeva. (2010). Classification of Coronary Damage in Chronic Chagasic Patients. In M. H.(eds) V. Sgurev (Ed.), Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence (Vol. 299, pp. 461–478). Springer-Verlag.
Abstract: Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
Keywords: Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding
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Jose Manuel Alvarez. (2010). Combining Context and Appearance for Road Detection (Antonio Lopez, & Theo Gevers, Eds.). Ph.D. thesis, Ediciones Graficas Rey, .
Abstract: Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the
development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit
color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene.
In this way, we present two different approaches to infer the geometry of the road ahead
the moving vehicle. Finally, we focus on combining these context and appearance (color)
approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art.
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Partha Pratim Roy. (2010). Multi-Oriented and Multi-Scaled Text Character Analysis and Recognition in Graphical Documents and their Applications to Document Image Retrieval (Josep Llados, & Umapada Pal, Eds.). Ph.D. thesis, Ediciones Graficas Rey, .
Abstract: With the advent research of Document Image Analysis and Recognition (DIAR), an
important line of research is explored on indexing and retrieval of graphics rich documents. It aims at finding relevant documents relying on segmentation and recognition
of text and graphics components underlying in non-standard layout where commercial
OCRs can not be applied due to complexity. This thesis is focused towards text information extraction approaches in graphical documents and retrieval of such documents
using text information.
Automatic text recognition in graphical documents (map, engineering drawing,
etc.) involves many challenges because text characters are usually printed in multioriented and multi-scale way along with different graphical objects. Text characters
are used to annotate the graphical curve lines and hence, many times they follow
curvi-linear paths too. For OCR of such documents, individual text lines and their
corresponding words/characters need to be extracted.
For recognition of multi-font, multi-scale and multi-oriented characters, we have
proposed a feature descriptor for character shape using angular information from contour pixels to take care of the invariance nature. To improve the efficiency of OCR, an
approach towards the segmentation of multi-oriented touching strings into individual
characters is also discussed. Convex hull based background information is used to
segment a touching string into possible primitive segments and later these primitive
segments are merged to get optimum segmentation using dynamic programming. To
overcome the touching/overlapping problem of text with graphical lines, a character
spotting approach using SIFT and skeleton information is included. Afterwards, we
propose a novel method to extract individual curvi-linear text lines using the foreground and background information of the characters of the text and a water reservoir
concept is used to utilize the background information.
We have also formulated the methodologies for graphical document retrieval applications using query words and seals. The retrieval approaches are performed using
recognition results of individual components in the document. Given a query text,
the system extracts positional knowledge from the query word and uses the same to
generate hypothetical locations in the document. Indexing of documents is also performed based on automatic detection of seals from documents containing cluttered
background. A seal is characterized by scale and rotation invariant spatial feature
descriptors computed from labelled text characters and a concept based on the Generalized Hough Transform is used to locate the seal in documents.
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