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Author |
Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Robust and accurate diaphragm border detection in cardiac X-Ray angiographies |
Type |
Conference Article |
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Year |
2012 |
Publication |
Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges |
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Volume |
7746 |
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Pages |
225-234 |
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Abstract |
Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods. |
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Nice, France |
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LNCS |
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0302-9743 |
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978-3-642-36960-5 |
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STACOM |
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MILAB |
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no |
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Call Number |
Admin @ si @ PRC2012 |
Serial |
2028 |
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Author |
Murad Al Haj; Jordi Gonzalez; Larry S. Davis |
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Title |
On Partial Least Squares in Head Pose Estimation: How to simultaneously deal with misalignment |
Type |
Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
2602-2609 |
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Abstract |
Head pose estimation is a critical problem in many computer vision applications. These include human computer interaction, video surveillance, face and expression recognition. In most prior work on heads pose estimation, the positions of the faces on which the pose is to be estimated are specified manually. Therefore, the results are reported without studying the effect of misalignment. We propose a method based on partial least squares (PLS) regression to estimate pose and solve the alignment problem simultaneously. The contributions of this paper are two-fold: 1) we show that the kernel version of PLS (kPLS) achieves better than state-of-the-art results on the estimation problem and 2) we develop a technique to reduce misalignment based on the learned PLS factors. |
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Providence, Rhode Island |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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ISE |
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no |
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Call Number |
Admin @ si @ HGD2012 |
Serial |
2029 |
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Author |
Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
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Title |
A New Image Dataset on Human Interactions |
Type |
Conference Article |
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Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
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Volume |
7378 |
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Pages |
204-209 |
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This article describes a new collection of still image dataset which are dedicated to interactions between people. Human action recognition from still images have been a hot topic recently, but most of them are actions performed by a single person, like running, walking, riding bikes, phoning and so on and there is no interactions between people in one image. The dataset collected in this paper are concentrating on human interaction between two people aiming to explore this new topic in the research area of action recognition from still images. |
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Address |
Mallorca |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-31566-4 |
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AMDO |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ GGT2012 |
Serial |
2030 |
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Author |
German Ros; Jesus Martinez del Rincon; Gines Garcia-Mateos |
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Title |
Articulated Particle Filter for Hand Tracking |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
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Pages |
3581 - 3585 |
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This paper proposes a new version of Particle Filter, called Articulated Particle Filter – ArPF -, which has been specifically designed for an efficient sampling of hierarchical spaces, generated by articulated objects. Our approach decomposes the articulated motion into layers for efficiency purposes, making use of a careful modeling of the diffusion noise along with its propagation through the articulations. This produces an increase of accuracy and prevent for divergences. The algorithm is tested on hand tracking due to its complex hierarchical articulated nature. With this purpose, a new dataset generation tool for quantitative evaluation is also presented in this paper. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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Conference |
ICPR |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RMG2012 |
Serial |
2031 |
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Permanent link to this record |
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Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
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Title |
Unsupervised co-segmentation through region matching |
Type |
Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
749-756 |
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Abstract |
Co-segmentation is defined as jointly partitioning multiple images depicting the same or similar object, into foreground and background. Our method consists of a multiple-scale multiple-image generative model, which jointly estimates the foreground and background appearance distributions from several images, in a non-supervised manner. In contrast to other co-segmentation methods, our approach does not require the images to have similar foregrounds and different backgrounds to function properly. Region matching is applied to exploit inter-image information by establishing correspondences between the common objects that appear in the scene. Moreover, computing many-to-many associations of regions allow further applications, like recognition of object parts across images. We report results on iCoseg, a challenging dataset that presents extreme variability in camera viewpoint, illumination and object deformations and poses. We also show that our method is robust against large intra-class variability in the MSRC database. |
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Providence, Rhode Island |
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IEEE Xplore |
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ISSN |
1063-6919 |
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978-1-4673-1226-4 |
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Conference |
CVPR |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ RSL2012b; ADAS @ adas @ |
Serial |
2033 |
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Permanent link to this record |
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Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
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Title |
Multiple target tracking and identity linking under split, merge and occlusion of targets and observations |
Type |
Conference Article |
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Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
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Address |
Algarve, Portugal |
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Conference |
ICPRAM |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RSL2012c; ADAS @ adas |
Serial |
2034 |
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Permanent link to this record |
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Author |
Ferran Diego; G.D. Evangelidis; Joan Serrat |
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Title |
Night-time outdoor surveillance by mobile cameras |
Type |
Conference Article |
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Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
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Volume |
2 |
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Pages |
365-371 |
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Abstract |
This paper addresses the problem of video surveillance by mobile cameras. We present a method that allows online change detection in night-time outdoor surveillance. Because of the camera movement, background frames are not available and must be “localized” in former sequences and registered with the current frames. To this end, we propose a Frame Localization And Registration (FLAR) approach that solves the problem efficiently. Frames of former sequences define a database which is queried by current frames in turn. To quickly retrieve nearest neighbors, database is indexed through a visual dictionary method based on the SURF descriptor. Furthermore, the frame localization is benefited by a temporal filter that exploits the temporal coherence of videos. Next, the recently proposed ECC alignment scheme is used to spatially register the synchronized frames. Finally, change detection methods apply to aligned frames in order to mark suspicious areas. Experiments with real night sequences recorded by in-vehicle cameras demonstrate the performance of the proposed method and verify its efficiency and effectiveness against other methods. |
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Algarve, Portugal |
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ICPRAM |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ DES2012 |
Serial |
2035 |
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Permanent link to this record |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru |
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Title |
Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs |
Type |
Conference Article |
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Year |
2011 |
Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging |
Abbreviated Journal |
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Volume |
7029 |
Issue |
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Pages |
223-230 |
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Abstract |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. |
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Address |
Nice, France |
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Springer Berlin Heidelberg |
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In H. Yoshida et al |
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ABDI |
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Notes |
IAM; MV |
Approved |
no |
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Call Number |
VGB2011 |
Serial |
2036 |
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Permanent link to this record |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title |
Synthetic ground truth dataset to detect shadow cast by static objects in outdoor |
Type |
Conference Article |
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Year |
2012 |
Publication |
1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications |
Abbreviated Journal |
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Pages |
art. 11 |
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Abstract |
In this paper, we propose a precise synthetic ground truth dataset to study the problem of detection of the shadows cast by static objects in outdoor environments during extended periods of time (days). For our dataset, we have created a virtual scenario using a rendering software. To increase the realism of the simulated environment, we have defined the scenario in a precise geographical location. In our dataset the sun is by far the main illumination source. The sun position during the simulation time takes into consideration factors related to the geographical location, such as the latitude, longitude, elevation above sea level, and precise image capturing day and time. In our simulation the camera remains fixed. The dataset consists of seven days of simulation, from 10:00am to 5:00pm. Images are captured every 10 seconds. The shadows' ground truth is automatically computed by the rendering software. |
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Address |
Capri, Italy |
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Publisher |
ACM |
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978-1-4503-1405-3 |
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Conference |
VIGTA |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ ISR2012a |
Serial |
2037 |
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Permanent link to this record |
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Author |
Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
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Title |
Supervised Brain Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
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Year |
2012 |
Publication |
High Performance Computing and Simulation, International Conference on |
Abbreviated Journal |
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Pages |
182-187 |
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Abstract |
This paper presents an automatic method for external and internal segmentation of the caudate nucleus in Magnetic Resonance Images (MRI) based on statistical and structural machine learning approaches. This method is applied in Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis. The external segmentation method adapts the Graph Cut energy-minimization model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus. In particular, new energy function data and boundary potentials are defined and a supervised energy term based on contextual brain structures is added. Furthermore, the internal segmentation method learns a classifier based on shape features of the Region of Interest (ROI) in MRI slices. The results show accurate external and internal caudate segmentation in a real data set and similar performance of ADHD diagnostic test to manual annotation. |
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Address |
Madrid |
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Publisher |
IEEE Xplore |
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978-1-4673-2359-8 |
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HPCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ ISH2012a |
Serial |
2038 |
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Permanent link to this record |
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Author |
Sergio Escalera |
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Title |
Human Behavior Analysis From Depth Maps |
Type |
Conference Article |
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Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
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Volume |
7378 |
Issue |
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Pages |
282-292 |
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Abstract |
Pose Recovery (PR) and Human Behavior Analysis (HBA) have been a main focus of interest from the beginnings of Computer Vision and Machine Learning. PR and HBA were originally addressed by the analysis of still images and image sequences. More recent strategies consisted of Motion Capture technology (MOCAP), based on the synchronization of multiple cameras in controlled environments; and the analysis of depth maps from Time-of-Flight (ToF) technology, based on range image recording from distance sensor measurements. Recently, with the appearance of the multi-modal RGBD information provided by the low cost Kinect \textsfTM sensor (from RGB and Depth, respectively), classical methods for PR and HBA have been redefined, and new strategies have been proposed. In this paper, the recent contributions and future trends of multi-modal RGBD data analysis for PR and HBA are reviewed and discussed. |
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Address |
Mallorca |
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Publisher |
Springer Heidelberg |
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Editor |
F.J. Perales; R.B. Fisher; T.B. Moeslund |
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0302-9743 |
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978-3-642-31566-4 |
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AMDO |
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Notes |
MILAB; HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ Esc2012 |
Serial |
2040 |
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Permanent link to this record |
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Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Three-Dimensional Design of Error Correcting Output Codes |
Type |
Conference Article |
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Year |
2012 |
Publication |
8th International Conference on Machine Learning and Data Mining |
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29- |
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Berlin, Germany |
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Conference |
MLDM |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ BGE2012a |
Serial |
2041 |
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Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Error Correcting Output Codes for multiclass classification: Application to two image vision problems |
Type |
Conference Article |
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Year |
2012 |
Publication |
16th symposium on Artificial Intelligence & Signal Processing |
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508-513 |
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Abstract |
Error-correcting output codes (ECOC) represents a powerful framework to deal with multiclass classification problems based on combining binary classifiers. The key factor affecting the performance of ECOC methods is the independence of binary classifiers, without which the ECOC method would be ineffective. In spite of its ability on classification of problems with relatively large number of classes, it has been applied in few real world problems. In this paper, we investigate the behavior of the ECOC approach on two image vision problems: logo recognition and shape classification using Decision Tree and AdaBoost as the base learners. The results show that the ECOC method can be used to improve the classification performance in comparison with the classical multiclass approaches. |
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Shiraz, Iran |
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IEEE Xplore |
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978-1-4673-1478-7 |
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AISP |
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HuPBA;MILAB |
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Admin @ si @ BGE2012b |
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2042 |
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Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Efficient pairwise classification using Local Cross Off strategy |
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Conference Article |
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2012 |
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25th Canadian Conference on Artificial Intelligence |
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7310 |
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25-36 |
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The pairwise classification approach tends to perform better than other well-known approaches when dealing with multiclass classification problems. In the pairwise approach, however, the nuisance votes of many irrelevant classifiers may result in a wrong prediction class. To overcome this problem, a novel method, Local Crossing Off (LCO), is presented and evaluated in this paper. The proposed LCO system takes advantage of nearest neighbor classification algorithm because of its simplicity and speed, as well as the strength of other two powerful binary classifiers to discriminate between two classes. This paper provides a set of experimental results on 20 datasets using two base learners: Neural Networks and Support Vector Machines. The results show that the proposed technique not only achieves better classification accuracy, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes. |
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Toronto, Ontario |
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0302-9743 |
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978-3-642-30352-4 |
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AI |
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HuPBA;MILAB |
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Admin @ si @ BGE2012c |
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2044 |
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Author |
Dimosthenis Karatzas;Ch. Lioutas |
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Software Package Development for Electron Diffraction Image Analysis |
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1998 |
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Proceedings of the XIV Solid State Physics National Conference |
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Ioannina, Greece |
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DAG |
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IAM @ iam @ KaL1998 |
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2045 |
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