Records |
Author |
Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu |
Title |
Estado del Arte en Sistemas de Vision Artificial para Personas Invidentes |
Type |
Journal |
Year |
2013 |
Publication |
Komputer Sapiens |
Abbreviated Journal |
KS |
Volume |
1 |
Issue |
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Pages |
20-25 |
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Notes |
OR;MV |
Approved |
no |
Call Number |
Admin @ si @ TSR2013 |
Serial |
2231 |
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Author |
Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa |
Title |
Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers |
Type |
Conference Article |
Year |
2013 |
Publication |
CVPR Workshop on Ground Truth – What is a good dataset? |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
688 - 693 |
Keywords |
Pedestrian Detection; Domain Adaptation |
Abstract |
Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. |
Address |
Portland; oregon; June 2013 |
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English |
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English |
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CVPRW |
Notes |
ADAS; 600.054; 600.057; 601.217 |
Approved |
yes |
Call Number |
XVR2013; ADAS @ adas @ xvr2013a |
Serial |
2220 |
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Author |
Ivet Rafegas |
Title |
Exploring Low-Level Vision Models. Case Study: Saliency Prediction |
Type |
Report |
Year |
2013 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
175 |
Issue |
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Thesis |
Master's thesis |
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CIC |
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no |
Call Number |
Admin @ si @ Raf2013 |
Serial |
2409 |
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Author |
Francesco Brughi |
Title |
Artistic Heritage Motive Retrieval: an Explorative Study |
Type |
Report |
Year |
2013 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
176 |
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Master's thesis |
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IAM |
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no |
Call Number |
Admin @ si @ Bru2013 |
Serial |
2410 |
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Author |
Bhaskar Chakraborty; Jordi Gonzalez; Xavier Roca |
Title |
Large scale continuous visual event recognition using max-margin Hough transformation framework |
Type |
Journal Article |
Year |
2013 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
Volume |
117 |
Issue |
10 |
Pages |
1356–1368 |
Keywords |
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Abstract |
In this paper we propose a novel method for continuous visual event recognition (CVER) on a large scale video dataset using max-margin Hough transformation framework. Due to high scalability, diverse real environmental state and wide scene variability direct application of action recognition/detection methods such as spatio-temporal interest point (STIP)-local feature based technique, on the whole dataset is practically infeasible. To address this problem, we apply a motion region extraction technique which is based on motion segmentation and region clustering to identify possible candidate “event of interest” as a preprocessing step. On these candidate regions a STIP detector is applied and local motion features are computed. For activity representation we use generalized Hough transform framework where each feature point casts a weighted vote for possible activity class centre. A max-margin frame work is applied to learn the feature codebook weight. For activity detection, peaks in the Hough voting space are taken into account and initial event hypothesis is generated using the spatio-temporal information of the participating STIPs. For event recognition a verification Support Vector Machine is used. An extensive evaluation on benchmark large scale video surveillance dataset (VIRAT) and as well on a small scale benchmark dataset (MSR) shows that the proposed method is applicable on a wide range of continuous visual event recognition applications having extremely challenging conditions. |
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ISSN |
1077-3142 |
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ISE |
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no |
Call Number |
Admin @ si @ CGR2013 |
Serial |
2413 |
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Author |
Ferran Poveda |
Title |
Computer Graphics and Vision Techniques for the Study of the Muscular Fiber Architecture of the Myocardium |
Type |
Book Whole |
Year |
2013 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Thesis |
Ph.D. thesis |
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Editor |
Debora Gil;Enric Marti |
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IAM |
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no |
Call Number |
Admin @ si @ Pov2013 |
Serial |
2417 |
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Author |
Mirko Arnold; Anarta Ghosh; Glen Doherty; Hugh Mulcahy; Stephen Patchett; Gerard Lacey |
Title |
Towards Automatic Direct Observation of Procedure and Skill (DOPS) in Colonoscopy |
Type |
Conference Article |
Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
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Volume |
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Issue |
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Pages |
48-53 |
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800 |
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VISIGRAPP |
Notes |
MV |
Approved |
no |
Call Number |
fernando @ fernando @ |
Serial |
2427 |
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Author |
Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier |
Title |
Speech balloon contour classification in comics |
Type |
Conference Article |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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Volume |
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Abstract |
Comic books digitization combined with subsequent comic book understanding create a variety of new applications, including mobile reading and data mining. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. In this work we detail a novel approach for classifying speech balloon in scanned comics book pages based on their contour time series. |
Address |
Bethlehem; PA; USA; August 2013 |
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GREC |
Notes |
DAG; 600.056 |
Approved |
no |
Call Number |
Admin @ si @ RKB2013 |
Serial |
2429 |
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Author |
J.S. Cope; P.Remagnino; S.Mannan; Katerine Diaz; Francesc J. Ferri; P.Wilkin |
Title |
Reverse Engineering Expert Visual Observations: From Fixations To The Learning Of Spatial Filters With A Neural-Gas Algorithm |
Type |
Journal Article |
Year |
2013 |
Publication |
Expert Systems with Applications |
Abbreviated Journal |
EXWA |
Volume |
40 |
Issue |
17 |
Pages |
6707-6712 |
Keywords |
Neural gas; Expert vision; Eye-tracking; Fixations |
Abstract |
Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give high responses to image regions which a human expert fixated on. These filters can then be used to identify regions in other images which are likely to be useful for a given vision task. The algorithm is evaluated by learning filters for locating specific areas of plant leaves. |
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0957-4174 |
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ADAS |
Approved |
no |
Call Number |
Admin @ si @ CRM2013 |
Serial |
2438 |
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Author |
Katerine Diaz; Francesc J. Ferri |
Title |
Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes |
Type |
Book Whole |
Year |
2013 |
Publication |
Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes |
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Los métodos basados en subespacios son una herramienta muy utilizada en aplicaciones de visión por computador. Aquí se presentan y validan algunos algoritmos que hemos propuesto en este campo de investigación. El primer algoritmo está relacionado con una extensión del método de vectores comunes discriminantes con kernel, que reinterpreta el espacio nulo de la matriz de dispersión intra-clase del conjunto de entrenamiento para obtener las características discriminantes. Dentro de los métodos basados en subespacios existen diferentes tipos de entrenamiento. Uno de los más populares, pero no por ello uno de los más eficientes, es el aprendizaje por lotes. En este tipo de aprendizaje, todas las muestras del conjunto de entrenamiento tienen que estar disponibles desde el inicio. De este modo, cuando nuevas muestras se ponen a disposición del algoritmo, el sistema tiene que ser reentrenado de nuevo desde cero. Una alternativa a este tipo de entrenamiento es el aprendizaje incremental. Aquí se proponen diferentes algoritmos incrementales del método de vectores comunes discriminantes. |
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978-3-639-55339-0 |
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ADAS |
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no |
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Admin @ si @ DiF2013 |
Serial |
2440 |
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Author |
Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez |
Title |
DA-DPM Pedestrian Detection |
Type |
Conference Article |
Year |
2013 |
Publication |
ICCV Workshop on Reconstruction meets Recognition |
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Domain Adaptation; Pedestrian Detection |
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ICCVW-RR |
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ADAS |
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no |
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Admin @ si @ XRV2013 |
Serial |
2569 |
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Author |
Marc Bolaños; Maite Garolera; Petia Radeva |
Title |
Active labeling application applied to food-related object recognition |
Type |
Conference Article |
Year |
2013 |
Publication |
5th International Workshop on Multimedia for Cooking & Eating Activities |
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Pages |
45-50 |
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Abstract |
Every day, lifelogging devices, available for recording different aspects of our daily life, increase in number, quality and functions, just like the multiple applications that we give to them. Applying wearable devices to analyse the nutritional habits of people is a challenging application based on acquiring and analyzing life records in long periods of time. However, to extract the information of interest related to the eating patterns of people, we need automatic methods to process large amount of life-logging data (e.g. recognition of food-related objects). Creating a rich set of manually labeled samples to train the algorithms is slow, tedious and subjective. To address this problem, we propose a novel method in the framework of Active Labeling for construct- ing a training set of thousands of images. Inspired by the hierarchical sampling method for active learning [6], we propose an Active forest that organizes hierarchically the data for easy and fast labeling. Moreover, introducing a classifier into the hierarchical structures, as well as transforming the feature space for better data clustering, additionally im- prove the algorithm. Our method is successfully tested to label 89.700 food-related objects and achieves significant reduction in expert time labelling.
Active labeling application applied to food-related object recognition ResearchGate. Available from: http://www.researchgate.net/publication/262252017Activelabelingapplicationappliedtofood-relatedobjectrecognition [accessed Jul 14, 2015]. |
Address |
Barcelona; October 2013 |
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ACM-CEA |
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MILAB |
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no |
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Admin @ si @ BGR2013b |
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2637 |
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Author |
Mohammad Rouhani; Angel Sappa |
Title |
The Richer Representation the Better Registration |
Type |
Journal Article |
Year |
2013 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
Volume |
22 |
Issue |
12 |
Pages |
5036-5049 |
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Abstract |
In this paper, the registration problem is formulated as a point to model distance minimization. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, this formulation avoids the correspondence search that is time-consuming. In the first stage, the target set is described through an implicit function by employing a linear least squares fitting. This function can be either an implicit polynomial or an implicit B-spline from a coarse to fine representation. In the second stage, we show how the obtained implicit representation is used as an interface to convert point-to-point registration into point-to-implicit problem. Furthermore, we show that this registration distance is smooth and can be minimized through the Levengberg-Marquardt algorithm. All the formulations presented for both stages are compact and easy to implement. In addition, we show that our registration method can be handled using any implicit representation though some are coarse and others provide finer representations; hence, a tradeoff between speed and accuracy can be set by employing the right implicit function. Experimental results and comparisons in 2D and 3D show the robustness and the speed of convergence of the proposed approach. |
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1057-7149 |
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ADAS |
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no |
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Admin @ si @ RoS2013 |
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2665 |
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Author |
Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados |
Title |
Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans |
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Conference Article |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.045; 600.061; 600.056 |
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no |
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Admin @ si @ HFF2013b |
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2695 |
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Author |
Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez |
Title |
Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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Bethlehem; PA; USA; August 2013 |
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DAG |
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no |
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Admin @ si @ HVS2013b |
Serial |
2696 |
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