| |
Records |
Links |
|
Author |
Jose Manuel Alvarez; Theo Gevers; Y. LeCun; Antonio Lopez |
|
| |
Title |
Road Scene Segmentation from a Single Image |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal  |
|
|
| |
Volume |
7578 |
Issue |
VII |
Pages |
376-389 |
|
| |
Keywords |
road detection |
|
| |
Abstract |
Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes provides relevant contextual information to improve their understanding.
In this paper, we use a convolutional neural network based algorithm to learn features from noisy labels to recover the 3D scene layout of a road image. The novelty of the algorithm relies on generating training labels by applying an algorithm trained on a general image dataset to classify on–board images. Further, we propose a novel texture descriptor based on a learned color plane fusion to obtain maximal uniformity in road areas. Finally, acquired (off–line) and current (on–line) information are combined to detect road areas in single images.
From quantitative and qualitative experiments, conducted on publicly available datasets, it is concluded that convolutional neural networks are suitable for learning 3D scene layout from noisy labels and provides a relative improvement of 7% compared to the baseline. Furthermore, combining color planes provides a statistical description of road areas that exhibits maximal uniformity and provides a relative improvement of 8% compared to the baseline. Finally, the improvement is even bigger when acquired and current information from a single image are combined |
|
| |
Address |
Florence, Italy |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-33785-7 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ECCV |
|
| |
Notes |
ADAS;ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ AGL2012; ADAS @ adas @ agl2012a |
Serial |
2022 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ivo Everts; Jan van Gemert; Theo Gevers |
|
| |
Title |
Per-patch Descriptor Selection using Surface and Scene Properties |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
|
|
| |
Volume |
7577 |
Issue |
VI |
Pages |
172-186 |
|
| |
Keywords |
|
|
| |
Abstract |
Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool. |
|
| |
Address |
Florence, Italy |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-33782-6 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ECCV |
|
| |
Notes |
ALTRES;ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ EGG2012 |
Serial |
2023 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah |
|
| |
Title |
Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
|
|
| |
Volume |
7574 |
Issue |
III |
Pages |
525-538 |
|
| |
Keywords |
|
|
| |
Abstract |
Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics. |
|
| |
Address |
Florence, Italy |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-33711-6 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ECCV |
|
| |
Notes |
ALTRES;ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DGS2012 |
Serial |
2024 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
|
| |
Title |
AVA: A Large-Scale Database for Aesthetic Visual Analysis |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
2408-2415 |
|
| |
Keywords |
|
|
| |
Abstract |
With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks |
|
| |
Address |
Providence, Rhode Islan |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CVPR |
|
| |
Notes |
CIC |
Approved |
no |
|
| |
Call Number |
Admin @ si @ MMP2012a |
Serial |
2025 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
|
| |
Title |
Names and Shades of Color for Intrinsic Image Estimation |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
278-285 |
|
| |
Keywords |
|
|
| |
Abstract |
In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance. |
|
| |
Address |
Providence, Rhode Island |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CVPR |
|
| |
Notes |
CIC |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SPB2012 |
Serial |
2026 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
|
| |
Title |
Learning to Rank Images using Semantic and Aesthetic Labels |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
23rd British Machine Vision Conference |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
110.1-110.10 |
|
| |
Keywords |
|
|
| |
Abstract |
Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one. |
|
| |
Address |
Guildford, London |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
1-901725-46-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
BMVC |
|
| |
Notes |
CIC |
Approved |
no |
|
| |
Call Number |
Admin @ si @ MMP2012b |
Serial |
2027 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta |
|
| |
Title |
Robust and accurate diaphragm border detection in cardiac X-Ray angiographies |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges |
Abbreviated Journal |
|
|
| |
Volume |
7746 |
Issue |
|
Pages |
225-234 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Nice, France |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-36960-5 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
STACOM |
|
| |
Notes |
MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PRC2012 |
Serial |
2028 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Murad Al Haj; Jordi Gonzalez; Larry S. Davis |
|
| |
Title |
On Partial Least Squares in Head Pose Estimation: How to simultaneously deal with misalignment |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
2602-2609 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Providence, Rhode Island |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CVPR |
|
| |
Notes |
ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ HGD2012 |
Serial |
2029 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
|
| |
Title |
A New Image Dataset on Human Interactions |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
| |
Volume |
7378 |
Issue |
|
Pages |
204-209 |
|
| |
Keywords |
|
|
| |
Abstract |
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. |
|
| |
Address |
Mallorca |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-31566-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
AMDO |
|
| |
Notes |
ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GGT2012 |
Serial |
2030 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
German Ros; Jesus Martinez del Rincon; Gines Garcia-Mateos |
|
| |
Title |
Articulated Particle Filter for Hand Tracking |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
3581 - 3585 |
|
| |
Keywords |
|
|
| |
Abstract |
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. |
|
| |
Address |
Tsukuba Science City, Japan |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RMG2012 |
Serial |
2031 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
|
| |
Title |
Unsupervised co-segmentation through region matching |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
749-756 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Providence, Rhode Island |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CVPR |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RSL2012b; ADAS @ adas @ |
Serial |
2033 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
|
| |
Title |
Multiple target tracking and identity linking under split, merge and occlusion of targets and observations |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Algarve, Portugal |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPRAM |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RSL2012c; ADAS @ adas |
Serial |
2034 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ferran Diego; G.D. Evangelidis; Joan Serrat |
|
| |
Title |
Night-time outdoor surveillance by mobile cameras |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
|
|
| |
Volume |
2 |
Issue |
|
Pages |
365-371 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Algarve, Portugal |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPRAM |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DES2012 |
Serial |
2035 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
|
| |
Title |
Synthetic ground truth dataset to detect shadow cast by static objects in outdoor |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
art. 11 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Capri, Italy |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
ACM |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-1-4503-1405-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
VIGTA |
|
| |
Notes |
OR;MV |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ISR2012a |
Serial |
2037 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
|
| |
Title |
Supervised Brain Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
High Performance Computing and Simulation, International Conference on |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
182-187 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Madrid |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-1-4673-2359-8 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
HPCS |
|
| |
Notes |
MILAB;HuPBA |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ISH2012a |
Serial |
2038 |
|
| Permanent link to this record |
