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Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
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Title |
Augmenting Video Surveillance Footage with Virtual Agents for Incremental Event Evaluation |
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Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
32 |
Issue |
6 |
Pages |
878–889 |
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Abstract |
The fields of segmentation, tracking and behavior analysis demand for challenging video resources to test, in a scalable manner, complex scenarios like crowded environments or scenes with high semantics. Nevertheless, existing public databases cannot scale the presence of appearing agents, which would be useful to study long-term occlusions and crowds. Moreover, creating these resources is expensive and often too particularized to specific needs. We propose an augmented reality framework to increase the complexity of image sequences in terms of occlusions and crowds, in a scalable and controllable manner. Existing datasets can be increased with augmented sequences containing virtual agents. Such sequences are automatically annotated, thus facilitating evaluation in terms of segmentation, tracking, and behavior recognition. In order to easily specify the desired contents, we propose a natural language interface to convert input sentences into virtual agent behaviors. Experimental tests and validation in indoor, street, and soccer environments are provided to show the feasibility of the proposed approach in terms of robustness, scalability, and semantics. |
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Elsevier |
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ISE |
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no |
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Admin @ si @ FBR2011b |
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1723 |
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Author |
Arjan Gijsenij; Theo Gevers |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Color Constancy Using Natural Image Statistics and Scene Semantics |
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Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
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Volume |
33 |
Issue |
4 |
Pages |
687-698 |
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Existing color constancy methods are all based on specific assumptions such as the spatial and spectral characteristics of images. As a consequence, no algorithm can be considered as universal. However, with the large variety of available methods, the question is how to select the method that performs best for a specific image. To achieve selection and combining of color constancy algorithms, in this paper natural image statistics are used to identify the most important characteristics of color images. Then, based on these image characteristics, the proper color constancy algorithm (or best combination of algorithms) is selected for a specific image. To capture the image characteristics, the Weibull parameterization (e.g., grain size and contrast) is used. It is shown that the Weibull parameterization is related to the image attributes to which the used color constancy methods are sensitive. An MoG-classifier is used to learn the correlation and weighting between the Weibull-parameters and the image attributes (number of edges, amount of texture, and SNR). The output of the classifier is the selection of the best performing color constancy method for a certain image. Experimental results show a large improvement over state-of-the-art single algorithms. On a data set consisting of more than 11,000 images, an increase in color constancy performance up to 20 percent (median angular error) can be obtained compared to the best-performing single algorithm. Further, it is shown that for certain scene categories, one specific color constancy algorithm can be used instead of the classifier considering several algorithms. |
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0162-8828 |
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ISE |
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Admin @ si @ GiG2011 |
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1724 |
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Author |
Albert Ali Salah; Theo Gevers; Nicu Sebe; Alessandro Vinciarelli |
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Title |
Computer Vision for Ambient Intelligence |
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Journal Article |
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Year |
2011 |
Publication |
Journal of Ambient Intelligence and Smart Environments |
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JAISE |
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3 |
Issue |
3 |
Pages |
187-191 |
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ISE |
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no |
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Admin @ si @ SGS2011a |
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1725 |
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Author |
Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln |
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Title |
Identifying Potentially Cancerous Tissues in Chromoendoscopy Images |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
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Pages |
709-716 |
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Keywords |
Endoscopy, Computer Assisted Diagnosis, Gradient. |
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Abstract |
The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered. |
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Las Palmas de Gran Canaria. Spain |
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Springer |
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Berlin |
Editor |
J. Vitria, J.M. Sanches, and M. Hernandez |
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LNCS |
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978-3-642-21256-7 |
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800 |
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IbPRIA |
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Notes |
MV;SIAI |
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no |
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Admin @ si @ RVD2011; IAM @ iam @ RVD2011 |
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1726 |
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Author |
Arnau Ramisa; Alex Goldhoorn; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas |
Type |
Journal Article |
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Year |
2011 |
Publication |
Journal of Intelligent and Robotic Systems |
Abbreviated Journal |
JIRC |
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Volume |
64 |
Issue |
3-4 |
Pages |
625-649 |
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Abstract |
Biologically inspired homing methods, such as the Average Landmark Vector, are an interesting solution for local navigation due to its simplicity. However, usually they require a modification of the environment by placing artificial landmarks in order to work reliably. In this paper we combine the Average Landmark Vector with invariant feature points automatically detected in panoramic images to overcome this limitation. The proposed approach has been evaluated first in simulation and, as promising results are found, also in two data sets of panoramas from real world environments. |
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Springer Netherlands |
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0921-0296 |
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RV;ADAS |
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no |
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Admin @ si @ RGA2011 |
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1728 |
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Author |
Koen E.A. van de Sande; Theo Gevers; Cees G.M. Snoek |
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Title |
Empowering Visual Categorization with the GPU |
Type |
Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Multimedia |
Abbreviated Journal |
TMM |
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Volume |
13 |
Issue |
1 |
Pages |
60-70 |
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Abstract |
Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the trend to increase computational power in newer CPU and GPU architectures is to increase their level of parallelism, exploiting this parallelism becomes an important direction to handle the computational cost of the bag-of-words approach. When optimizing a system based on the bag-of-words approach, the goal is to minimize the time it takes to process batches of images. Additionally, we also consider power usage as an evaluation metric. In this paper, we analyze the bag-of-words model for visual categorization in terms of computational cost and identify two major bottlenecks: the quantization step and the classification step. We address these two bottlenecks by proposing two efficient algorithms for quantization and classification by exploiting the GPU hardware and the CUDA parallel programming model. The algorithms are designed to (1) keep categorization accuracy intact, (2) decompose the problem and (3) give the same numerical results. In the experiments on large scale datasets it is shown that, by using a parallel implementation on the Geforce GTX260 GPU, classifying unseen images is 4.8 times faster than a quad-core CPU version on the Core i7 920, while giving the exact same numerical results. In addition, we show how the algorithms can be generalized to other applications, such as text retrieval and video retrieval. Moreover, when the obtained speedup is used to process extra video frames in a video retrieval benchmark, the accuracy of visual categorization is improved by 29%. |
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ISE |
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no |
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Admin @ si @ SGS2011b |
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1729 |
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Author |
Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez |
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Title |
Pattern Recognition and Image Analysis |
Type |
Book Whole |
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Year |
2011 |
Publication |
5th Iberian Conference Pattern Recognition and Image Analysis |
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Volume |
6669 |
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Las Palmas de Gran Canaria. Spain |
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Springer-Verlag |
Place of Publication |
Berlin |
Editor |
J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
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978-3-642-2125 |
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IbPRIA |
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OR;MV |
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no |
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Call Number |
Admin @ si @ VSR2011 |
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1730 |
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Author |
Mario Rojas; David Masip; Jordi Vitria |
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Title |
Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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6669 |
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371-378 |
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Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. |
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Las Palmas de Gran Canaria. Spain |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-21256-7 |
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IbPRIA |
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OR;MV |
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no |
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Call Number |
Admin @ si @ RMV2011a |
Serial |
1731 |
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Permanent link to this record |
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Author |
Jon Almazan; Ernest Valveny; Alicia Fornes |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
1-8 |
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Abstract |
This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance. |
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Las Palmas de Gran Canaria. Spain |
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Springer-Verlag |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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LNCS |
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IbPRIA |
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DAG; |
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no |
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Admin @ si @ AVF2011 |
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1732 |
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Author |
Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich |
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Title |
Perception Based Representations for Computational Colour |
Type |
Conference Article |
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Year |
2011 |
Publication |
3rd International Workshop on Computational Color Imaging |
Abbreviated Journal |
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Volume |
6626 |
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Pages |
16-30 |
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colour perception, induction, naming, psychophysical data, saliency, segmentation |
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Abstract |
The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. |
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Milan, Italy |
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Springer-Verlag |
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Raimondo Schettini, Shoji Tominaga, Alain Trémeau |
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LNCS |
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978-3-642-20403-6 |
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CCIW |
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CIC |
Approved |
no |
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Admin @ si @ VMB2011 |
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1733 |
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Permanent link to this record |
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Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria; Petia Radeva |
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Title |
Interactive Labeling of WCE Images |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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143-150 |
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A high quality labeled training set is necessary for any supervised machine learning algorithm. Labeling of the data can be a very expensive process, specially while dealing with data of high variability and complexity. A good example of such data are the videos from Wireless Capsule Endoscopy. Building a representative WCE data set means many videos to be labeled by an expert. The problem that occurs is the data diversity, in the space of the features, from different WCE studies. That means that when new data arrives it is highly probable that it will not be represented in the training set, thus getting a high probability of performing an error when applying machine learning schemes. In this paper an interactive labeling scheme that allows reducing expert effort in the labeling process is presented. It is shown that the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of the WCE video with less than 100 clicks |
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Las Palmas de Gran Canaria. Spain |
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Springer |
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Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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IbPRIA |
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MILAB;OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ DSM2011 |
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1734 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Human Activity Recognition from Accelerometer Data using a Wearable Device |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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289-296 |
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Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%. |
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Las Palmas de Gran Canaria. Spain |
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Springer Berlin Heidelberg |
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Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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LNCS |
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0302-9743 |
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978-3-642-21256-7 |
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IbPRIA |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPR2011a |
Serial |
1735 |
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Author |
Lluis Pere de las Heras; Gemma Sanchez |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
17-24 |
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Abstract |
This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction. |
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Address |
Las Palmas de Gran Canaria. Spain |
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978-3-642-21256-7 |
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IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ HeS2011 |
Serial |
1736 |
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Author |
Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval |
Type |
Conference Article |
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Year |
2011 |
Publication |
33rd European Conference on Information Retrieval |
Abbreviated Journal |
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Volume |
6611 |
Issue |
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Pages |
314-325 |
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Abstract |
In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset. |
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Address |
Dublin, Ireland |
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Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
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LNCS |
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ISBN |
978-3-642-20160-8 |
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ECIR |
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Notes |
DAG; RV;ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RAK2011 |
Serial |
1737 |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
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Title |
A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
620-627 |
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Abstract |
In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ DLP2011a |
Serial |
1738 |
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Permanent link to this record |