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Author |
Robert Benavente; C. Alejandro Parraga; Maria Vanrell |
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Title |
La influencia del contexto en la definicion de las fronteras entre las categorias cromaticas |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th Congreso Nacional del Color |
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Pages |
92–95 |
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Categorización del color; Apariencia del color; Influencia del contexto; Patrones de Mondrian; Modelos paramétricos |
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Abstract |
En este artículo presentamos los resultados de un experimento de categorización de color en el que las muestras se presentaron sobre un fondo multicolor (Mondrian) para simular los efectos del contexto. Los resultados se comparan con los de un experimento previo que, utilizando un paradigma diferente, determinó las fronteras sin tener en cuenta el contexto. El análisis de los resultados muestra que las fronteras obtenidas con el experimento en contexto presentan menos confusión que las obtenidas en el experimento sin contexto. |
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Alicante (Spain) |
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978-84-9717-144-1 |
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CNC |
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CIC |
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no |
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CAT @ cat @ BPV2010 |
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1327 |
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Author |
Naila Murray; Eduard Vazquez |
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Title |
Lacuna Restoration: How to choose a neutral colour? |
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Conference Article |
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Year |
2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
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248–252 |
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Painting restoration which involves filling in material loss (called lacuna) is a complex process. Several standard techniques exist to tackle lacuna restoration,
and this article focuses on those techniques that employ a “neutral” colour to mask the defect. Restoration experts often disagree on the choice of such a colour and in fact, the concept of a neutral colour is controversial. We posit that a neutral colour is one that attracts relatively little visual attention for a specific lacuna. We conducted an eye tracking experiment to compare two common neutral
colour selection methods, specifically the most common local colour and the mean local colour. Results obtained demonstrate that the most common local colour triggers less visual attention in general. Notwithstanding, we have observed instances in which the most common colour triggers a significant amount of attention when subjects spent time resolving their confusion about whether or not a lacuna was part of the painting. |
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Gjovik, Norway |
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CREATE |
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no |
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Admin @ si @ MuV2010 |
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1297 |
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Author |
Javier Marin; David Vazquez; David Geronimo; Antonio Lopez |
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Title |
Learning Appearance in Virtual Scenarios for Pedestrian Detection |
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Conference Article |
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Year |
2010 |
Publication |
23rd IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
137–144 |
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Pedestrian Detection; Domain Adaptation |
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Detecting pedestrians in images is a key functionality to avoid vehicle-to-pedestrian collisions. The most promising detectors rely on appearance-based pedestrian classifiers trained with labelled samples. This paper addresses the following question: can a pedestrian appearance model learnt in virtual scenarios work successfully for pedestrian detection in real images? (Fig. 1). Our experiments suggest a positive answer, which is a new and relevant conclusion for research in pedestrian detection. More specifically, we record training sequences in virtual scenarios and then appearance-based pedestrian classifiers are learnt using HOG and linear SVM. We test such classifiers in a publicly available dataset provided by Daimler AG for pedestrian detection benchmarking. This dataset contains real world images acquired from a moving car. The obtained result is compared with the one given by a classifier learnt using samples coming from real images. The comparison reveals that, although virtual samples were not specially selected, both virtual and real based training give rise to classifiers of similar performance. |
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San Francisco; CA; USA; June 2010 |
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English |
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English |
Original Title |
Learning Appearance in Virtual Scenarios for Pedestrian Detection |
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1063-6919 |
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978-1-4244-6984-0 |
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CVPR |
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ADAS |
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no |
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ADAS @ adas @ MVG2010 |
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1304 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Learning photometric invariance for object detection |
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Journal Article |
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Year |
2010 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
90 |
Issue |
1 |
Pages |
45-61 |
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Keywords |
road detection |
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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 |
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Springer US |
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0920-5691 |
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ADAS;ISE |
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no |
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ADAS @ adas @ AGL2010c |
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1451 |
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Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell |
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Title |
Local Perceptual Weighting in JPEG2000 for Color Images |
Type |
Conference Article |
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Year |
2010 |
Publication |
5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
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255–260 |
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The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM (Chromatic Induction Wavelet Model). |
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Joensuu, Finland |
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9781617388897 |
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CGIV/MCS |
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CIC |
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no |
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Call Number |
CAT @ cat @ MOV2010a |
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1307 |
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Author |
Debora Gil; Jaume Garcia; Aura Hernandez-Sabate; Enric Marti |
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Title |
Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy |
Type |
Conference Article |
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Year |
2010 |
Publication |
8th Medical Imaging |
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Volume |
7623 |
Issue |
762304 |
Pages |
304 |
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Abstract |
Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature. |
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SPIE |
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SPIE |
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IAM |
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no |
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IAM @ iam @ GGH2010a |
Serial |
1522 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
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Title |
Method for automatic classification of in vivo images |
Type |
Patent |
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Year |
2010 |
Publication |
US 2010/0046816 |
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A method for automatically detecting a post-duodenal boundary in an image stream of the gastrointestinal (GI) tract. The image stream is sampled to obtain a reduced set of images for processing. The reduced set of images is filtered to remove non-valid frames or non-valid portions of frames, thereby generating a filtered set of valid images. A polar representation of the valid images is generated. Textural features of the polar representation are processed to detect the post-duodenal boundary of the GI tract. |
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800 |
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Notes |
MV;OR;MILAB;SIAI |
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no |
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Call Number |
IAM @ iam @ VSR2010 |
Serial |
1702 |
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Author |
Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu |
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Title |
Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks |
Type |
Conference Article |
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Year |
2010 |
Publication |
12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. |
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Social interaction; Multimodal fusion, Influence model; Social network analysis |
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Abstract |
Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters
are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented
mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states
encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results
are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network. |
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Beijing (China) |
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ICMI-MLI |
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Notes |
OR;MILAB;HUPBA;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ ERV2010 |
Serial |
1427 |
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Author |
Ignasi Rius |
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Title |
Motion Priors for Efficient Bayesian Tracking in Human Sequence Evaluation |
Type |
Book Whole |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Recovering human motion by visual analysis is a challenging computer vision research
area with a lot of potential applications. Model-based tracking approaches, and in
particular particle lters, formulate the problem as a Bayesian inference task whose
aim is to sequentially estimate the distribution of the parameters of a human body
model over time. These approaches strongly rely on good dynamical and observation
models to predict and update congurations of the human body according to measurements from the image data. However, it is very dicult to design observation
models which extract useful and reliable information from image sequences robustly.
This results specially challenging in monocular tracking given that only one viewpoint
from the scene is available. Therefore, to overcome these limitations strong motion
priors are needed to guide the exploration of the state space.
The work presented in this Thesis is aimed to retrieve the 3D motion parameters
of a human body model from incomplete and noisy measurements of a monocular
image sequence. These measurements consist of the 2D positions of a reduced set of
joints in the image plane. Towards this end, we present a novel action-specic model
of human motion which is trained from several databases of real motion-captured
performances of an action, and is used as a priori knowledge within a particle ltering
scheme.
Body postures are represented by means of a simple and compact stick gure
model which uses direction cosines to represent the direction of body limbs in the 3D
Cartesian space. Then, for a given action, Principal Component Analysis is applied to
the training data to perform dimensionality reduction over the highly correlated input
data. Before the learning stage of the action model, the input motion performances
are synchronized by means of a novel dense matching algorithm based on Dynamic
Programming. The algorithm synchronizes all the motion sequences of the same
action class, nding an optimal solution in real-time.
Then, a probabilistic action model is learnt, based on the synchronized motion
examples, which captures the variability and temporal evolution of full-body motion
within a specic action. In particular, for each action, the parameters learnt are: a
representative manifold for the action consisting of its mean performance, the standard deviation from the mean performance, the mean observed direction vectors from
each motion subsequence of a given length and the expected error at a given time
instant.
Subsequently, the action-specic model is used as a priori knowledge on human
motion which improves the eciency and robustness of the overall particle filtering tracking framework. First, the dynamic model guides the particles according to similar
situations previously learnt. Then, the state space is constrained so only feasible
human postures are accepted as valid solutions at each time step. As a result, the
state space is explored more eciently as the particle set covers the most probable
body postures.
Finally, experiments are carried out using test sequences from several motion
databases. Results point out that our tracker scheme is able to estimate the rough
3D conguration of a full-body model providing only the 2D positions of a reduced
set of joints. Separate tests on the sequence synchronization method and the subsequence probabilistic matching technique are also provided. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Jordi Gonzalez;Xavier Roca |
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978-84-937261-9-5 |
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no |
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Call Number |
Admin @ si @ Riu2010 |
Serial |
1331 |
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Author |
Partha Pratim Roy |
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Title |
Multi-Oriented and Multi-Scaled Text Character Analysis and Recognition in Graphical Documents and their Applications to Document Image Retrieval |
Type |
Book Whole |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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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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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Josep Llados;Umapada Pal |
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978-84-937261-7-1 |
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Approved |
no |
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Call Number |
Admin @ si @ Roy2010 |
Serial |
1455 |
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Permanent link to this record |
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Author |
Umapada Pal; Partha Pratim Roy; N. Tripathya; Josep Llados |
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Title |
Multi-oriented Bangla and Devnagari text recognition |
Type |
Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
43 |
Issue |
12 |
Pages |
4124–4136 |
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Keywords |
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Abstract |
There are printed complex documents where text lines of a single page may have different orientations or the text lines may be curved in shape. As a result, it is difficult to detect the skew of such documents and hence character segmentation and recognition of such documents are a complex task. In this paper, using background and foreground information we propose a novel scheme towards the recognition of Indian complex documents of Bangla and Devnagari script. In Bangla and Devnagari documents usually characters in a word touch and they form cavity regions. To take care of these cavity regions, background information of such documents is used. Convex hull and water reservoir principle have been applied for this purpose. Here, at first, the characters are segmented from the documents using the background information of the text. Next, individual characters are recognized using rotation invariant features obtained from the foreground part of the characters.
For character segmentation, at first, writing mode of a touching component (word) is detected using water reservoir principle based features. Next, depending on writing mode and the reservoir base-region of the touching component, a set of candidate envelope points is then selected from the contour points of the component. Based on these candidate points, the touching component is finally segmented into individual characters. For recognition of multi-sized/multi-oriented characters the features are computed from different angular information obtained from the external and internal contour pixels of the characters. These angular information are computed in such a way that they do not depend on the size and rotation of the characters. Circular and convex hull rings have been used to divide a character into smaller zones to get zone-wise features for higher recognition results. We combine circular and convex hull features to improve the results and these features are fed to support vector machines (SVM) for recognition. From our experiment we obtained recognition results of 99.18% (98.86%) accuracy when tested on 7515 (7874) Devnagari (Bangla) characters. |
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Elsevier |
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DAG |
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DAG @ dag @ PRT2010 |
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1337 |
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Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |
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Title |
Multimodal Template Matching based on Gradient and Mutual Information using Scale-Space |
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Conference Article |
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Year |
2010 |
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17th IEEE International Conference on Image Processing |
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2749–2752 |
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This paper presents the combined use of gradient and mutual information for infrared and intensity templates matching. We propose to joint: (i) feature matching in a multiresolution context and (ii) information propagation through scale-space representations. Our method consists in combining mutual information with a shape descriptor based on gradient, and propagate them following a coarse-to-fine strategy. The main contributions of this work are: to offer a theoretical formulation towards a multimodal stereo matching; to show that gradient and mutual information can be reinforced while they are propagated between consecutive levels; and to show that they are valid cost functions in multimodal template matchings. Comparisons are presented showing the improvements and viability of the proposed approach. |
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Hong-Kong |
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1522-4880 |
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978-1-4244-7992-4 |
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ICIP |
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ADAS |
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no |
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ADAS @ adas @ BLS2010 |
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1358 |
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Author |
Jaume Amores; David Geronimo; Antonio Lopez |
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Multiple instance and active learning for weakly-supervised object-class segmentation |
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Conference Article |
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2010 |
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3rd IEEE International Conference on Machine Vision |
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Multiple Instance Learning; Active Learning; Object-class segmentation. |
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In object-class segmentation, one of the most tedious tasks is to manually segment many object examples in order to learn a model of the object category. Yet, there has been little research on reducing the degree of manual annotation for
object-class segmentation. In this work we explore alternative strategies which do not require full manual segmentation of the object in the training set. In particular, we study the use of bounding boxes as a coarser and much cheaper form of segmentation and we perform a comparative study of several Multiple-Instance Learning techniques that allow to obtain a model with this type of weak annotation. We show that some of these methods can be competitive, when used with coarse
segmentations, with methods that require full manual segmentation of the objects. Furthermore, we show how to use active learning combined with this weakly supervised strategy.
As we see, this strategy permits to reduce the amount of annotation and optimize the number of examples that require full manual segmentation in the training set. |
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Hong-Kong |
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ICMV |
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ADAS |
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no |
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ADAS @ adas @ AGL2010b |
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1429 |
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Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez; Daniel Ponsa |
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Title |
Multiple-target tracking for the intelligent headlights control |
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Conference Article |
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2010 |
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13th Annual International Conference on Intelligent Transportation Systems |
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903–910 |
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Intelligent Headlights |
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TA7.4
Intelligent vehicle lighting systems aim at automatically regulating the headlights' beam to illuminate as much of the road ahead as possible while avoiding dazzling other drivers. A key component of such a system is computer vision software that is able to distinguish blobs due to vehicles' headlights and rear lights from those due to road lamps and reflective elements such as poles and traffic signs. In a previous work, we have devised a set of specialized supervised classifiers to make such decisions based on blob features related to its intensity and shape. Despite the overall good performance, there remain challenging that have yet to be solved: notably, faint and tiny blobs corresponding to quite distant vehicles. In fact, for such distant blobs, classification decisions can be taken after observing them during a few frames. Hence, incorporating tracking could improve the overall lighting system performance by enforcing the temporal consistency of the classifier decision. Accordingly, this paper focuses on the problem of constructing blob tracks, which is actually one of multiple-target tracking (MTT), but under two special conditions: We have to deal with frequent occlusions, as well as blob splits and merges. We approach it in a novel way by formulating the problem as a maximum a posteriori inference on a Markov random field. The qualitative (in video form) and quantitative evaluation of our new MTT method shows good tracking results. In addition, we will also see that the classification performance of the problematic blobs improves due to the proposed MTT algorithm. |
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Madeira Island (Portugal) |
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ITSC |
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ADAS |
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no |
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ADAS @ adas @ RSL2010 |
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1422 |
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Author |
Marta Teres; Eduard Vazquez |
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Title |
Museums, spaces and museographical resources. Current state and proposals for a multidisciplinary framework to open new perspectives |
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Conference Article |
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2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
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319–323 |
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Two of the main aims of a museum are to communicate its heritage and to make enjoy its visitors. This communication can be done through the pieces itself and the museographical resources but also through the building, the interior design, the light and the colour. Art museums, in opposition with other museums, lack on the application of these additional resources. Such a work necessarily requires a multidisciplinary point of view for a holistic vision of all what a museum implies and to use all its potential as a tool of knowledge and culture for all the visitors. |
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Gjovik, Norway |
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CREATE |
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Admin @ si @ TeV2010 |
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1298 |
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