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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 |
Type |
Book Whole |
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Year |
2012 |
Publication |
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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Editor |
F. Javier Sanchez;Fernando Vilariño |
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800 |
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MV |
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no |
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Call Number |
Admin @ si @ Ber2012 |
Serial |
2211 |
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Author |
Naila Murray |
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Title |
Predicting Saliency and Aesthetics in Images: A Bottom-up Perspective |
Type |
Book Whole |
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Year |
2012 |
Publication |
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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Publisher |
Ediciones Graficas Rey |
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Editor |
Xavier Otazu;Maria Vanrell |
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CIC |
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no |
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Call Number |
Admin @ si @ Mur2012 |
Serial |
2212 |
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Author |
Marina Alberti |
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Title |
Detection and Alignment of Vascular Structures in Intravascular Ultrasound using Pattern Recognition Techniques |
Type |
Book Whole |
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Year |
2013 |
Publication |
PhD Thesis, Universitat de Barcelona-CVC |
Abbreviated Journal |
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In this thesis, several methods for the automatic analysis of Intravascular Ultrasound
(IVUS) sequences are presented, aimed at assisting physicians in the diagnosis, the assessment of the intervention and the monitoring of the patients with coronary disease.
The basis for the developed frameworks are machine learning, pattern recognition and
image processing techniques.
First, a novel approach for the automatic detection of vascular bifurcations in
IVUS is presented. The task is addressed as a binary classi cation problem (identifying bifurcation and non-bifurcation angular sectors in the sequence images). The
multiscale stacked sequential learning algorithm is applied, to take into account the
spatial and temporal context in IVUS sequences, and the results are re ned using
a-priori information about branching dimensions and geometry. The achieved performance is comparable to intra- and inter-observer variability.
Then, we propose a novel method for the automatic non-rigid alignment of IVUS
sequences of the same patient, acquired at dierent moments (before and after percutaneous coronary intervention, or at baseline and follow-up examinations). The
method is based on the description of the morphological content of the vessel, obtained by extracting temporal morphological pro les from the IVUS acquisitions, by
means of methods for segmentation, characterization and detection in IVUS. A technique for non-rigid sequence alignment – the Dynamic Time Warping algorithm -
is applied to the pro les and adapted to the speci c clinical problem. Two dierent robust strategies are proposed to address the partial overlapping between frames
of corresponding sequences, and a regularization term is introduced to compensate
for possible errors in the pro le extraction. The bene ts of the proposed strategy
are demonstrated by extensive validation on synthetic and in-vivo data. The results
show the interest of the proposed non-linear alignment and the clinical value of the
method.
Finally, a novel automatic approach for the extraction of the luminal border in
IVUS images is presented. The method applies the multiscale stacked sequential
learning algorithm and extends it to 2-D+T, in a rst classi cation phase (the identi-
cation of lumen and non-lumen regions of the images), while an active contour model
is used in a second phase, to identify the lumen contour. The method is extended
to the longitudinal dimension of the sequences and it is validated on a challenging
data-set. |
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Address |
Barcelona |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Simone Balocco;Petia Radeva |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ Alb2013 |
Serial |
2215 |
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Author |
Sergio Escalera |
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Title |
Coding and Decoding Design of ECOCs for Multi-class Pattern and Object Recognition A |
Type |
Book Whole |
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Year |
2008 |
Publication |
PhD Thesis, Universitat de Barcelona-CVC |
Abbreviated Journal |
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Abstract |
Many real problems require multi-class decisions. In the Pattern Recognition field,
many techniques have been proposed to deal with the binary problem. However,
the extension of many 2-class classifiers to the multi-class case is a hard task. In
this sense, Error-Correcting Output Codes (ECOC) demonstrated to be a powerful
tool to combine any number of binary classifiers to model multi-class problems. But
there are still many open issues about the capabilities of the ECOC framework. In
this thesis, the two main stages of an ECOC design are analyzed: the coding and
the decoding steps. We present different problem-dependent designs. These designs
take advantage of the knowledge of the problem domain to minimize the number
of classifiers, obtaining a high classification performance. On the other hand, we
analyze the ECOC codification in order to define new decoding rules that take full
benefit from the information provided at the coding step. Moreover, as a successful
classification requires a rich feature set, new feature detection/extraction techniques
are presented and evaluated on the new ECOC designs. The evaluation of the new
methodology is performed on different real and synthetic data sets: UCI Machine
Learning Repository, handwriting symbols, traffic signs from a Mobile Mapping System, Intravascular Ultrasound images, Caltech Repository data set or Chaga’s disease
data set. The results of this thesis show that significant performance improvements
are obtained on both traditional coding and decoding ECOC designs when the new
coding and decoding rules are taken into account. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Petia Radeva;Oriol Pujol |
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Notes |
MILAB; HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ Esc2008b |
Serial |
2217 |
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Author |
David Augusto Rojas |
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Title |
Colouring Local Feature Detection for Matching |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
133 |
Issue |
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Pages |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Publisher |
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Place of Publication |
Bellaterra, Barcelona |
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Notes |
CIC |
Approved |
no |
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Call Number |
Admin @ si @ Roj2009 |
Serial |
2392 |
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Author |
Juan Diego Gomez |
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Title |
Toward Robust Myocardial Blush Grade Estimation in Contrast Angiography |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
134 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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MILAB |
Approved |
no |
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Call Number |
Admin @ si @ Gom2009 |
Serial |
2393 |
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Author |
Olivier Penacchio |
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Title |
Relative Density of L, M, S photoreceptors in the Human Retina |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
135 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Pen2009 |
Serial |
2394 |
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Author |
Xavier Boix |
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Title |
Learning Conditional Random Fields for Stereo |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
136 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Boi2009 |
Serial |
2395 |
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Author |
Shida Beigpour |
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Title |
Physics-based Reflectance Estimation Applied to Recoloring |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
137 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
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no |
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Call Number |
Admin @ si @ Bei2009 |
Serial |
2396 |
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Author |
Jaume Gibert |
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Title |
Learning structural representations and graph matching paradigms in the context of object recognition |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
143 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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DAG |
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no |
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Call Number |
Admin @ si @ Gib2009 |
Serial |
2397 |
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Author |
Jose Carlos Rubio |
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Title |
Graph matching based on graphical models with application to vehicle tracking and classification at night |
Type |
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Year |
2009 |
Publication |
CVC Technical Report |
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144 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
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no |
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Call Number |
Admin @ si @ Rub2009 |
Serial |
2398 |
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Author |
Farshad Nourbakhsh |
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Title |
Colour logo recognition |
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Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
145 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ Nou2009 |
Serial |
2399 |
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Author |
Enric Sala |
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Title |
Off-line person-dependent signature verification |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
146 |
Issue |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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Approved |
no |
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Call Number |
Admin @ si @ Sal2009 |
Serial |
2400 |
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Author |
Wenjuan Gong |
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Title |
Action priors for human pose tracking by particle filter |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ Gon2009 |
Serial |
2401 |
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| Permanent link to this record |
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Author |
Diego Alejandro Cheda |
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Title |
Monocular egomotion estimation for ADAS application |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
148 |
Issue |
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Pages |
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Keywords |
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Abstract |
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Address |
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Corporate Author |
Computer Vision Center |
Thesis |
Ph.D. thesis |
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Publisher |
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Place of Publication |
Bellaterra, Barcelona |
Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Che2009 |
Serial |
2402 |
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| Permanent link to this record |
