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Author |
Jose Manuel Alvarez; Theo Gevers; Y. LeCun; Antonio Lopez |
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Title |
Road Scene Segmentation from a Single Image |
Type |
Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
7578 |
Issue |
VII |
Pages |
376-389 |
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Keywords |
road detection |
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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 |
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Florence, Italy |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-33785-7 |
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ECCV |
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ADAS;ISE |
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no |
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Admin @ si @ AGL2012; ADAS @ adas @ agl2012a |
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2022 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Feature Selection on Node Statistics Based Embedding of Graphs |
Type |
Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
33 |
Issue |
15 |
Pages |
1980–1990 |
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Keywords |
Structural pattern recognition; Graph embedding; Feature ranking; PCA; Graph classification |
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Abstract |
Representing a graph with a feature vector is a common way of making statistical machine learning algorithms applicable to the domain of graphs. Such a transition from graphs to vectors is known as graphembedding. A key issue in graphembedding is to select a proper set of features in order to make the vectorial representation of graphs as strong and discriminative as possible. In this article, we propose features that are constructed out of frequencies of node label representatives. We first build a large set of features and then select the most discriminative ones according to different ranking criteria and feature transformation algorithms. On different classification tasks, we experimentally show that only a small significant subset of these features is needed to achieve the same classification rates as competing to state-of-the-art methods. |
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DAG |
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no |
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Admin @ si @ GVB2012b |
Serial |
1993 |
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Author |
Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez |
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Title |
Selective Spatio-Temporal Interest Points |
Type |
Journal Article |
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Year |
2012 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
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Volume |
116 |
Issue |
3 |
Pages |
396-410 |
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Abstract |
Recent progress in the field of human action recognition points towards the use of Spatio-TemporalInterestPoints (STIPs) for local descriptor-based recognition strategies. In this paper, we present a novel approach for robust and selective STIP detection, by applying surround suppression combined with local and temporal constraints. This new method is significantly different from existing STIP detection techniques and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-video words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on popular benchmark datasets (KTH and Weizmann), more challenging datasets of complex scenes with background clutter and camera motion (CVC and CMU), movie and YouTube video clips (Hollywood 2 and YouTube), and complex scenes with multiple actors (MSR I and Multi-KTH), validates our approach and show state-of-the-art performance. Due to the unavailability of ground truth action annotation data for the Multi-KTH dataset, we introduce an actor specific spatio-temporal clustering of STIPs to address the problem of automatic action annotation of multiple simultaneous actors. Additionally, we perform cross-data action recognition by training on source datasets (KTH and Weizmann) and testing on completely different and more challenging target datasets (CVC, CMU, MSR I and Multi-KTH). This documents the robustness of our proposed approach in the realistic scenario, using separate training and test datasets, which in general has been a shortcoming in the performance evaluation of human action recognition techniques. |
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Elsevier |
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ISSN |
1077-3142 |
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ISE |
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no |
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Call Number |
Admin @ si @ CHM2012 |
Serial |
1806 |
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Author |
Fernando Barrera |
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Title |
Multimodal Stereo from Thermal Infrared and Visible Spectrum |
Type |
Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Abstract |
Recent advances in thermal infrared imaging (LWIR) has allowed its use in applications beyond of the military domain. Nowadays, this new family of sensors is included in different technical and scientific applications. They offer features that facilitate tasks, such as detection of pedestrians, hot spots, differences in temperature, among others, which can significantly improve the performance of a system where the persons are expected to play the principal role. For instance, video surveillance applications, monitoring, and pedestrian detection.
During this dissertation the next question is stated: Could a couple of sensors measuring different bands of the electromagnetic spectrum, as the visible and thermal infrared, be used to extract depth information? Although it is a complex question, we shows that a system of these characteristics is possible as well as their advantages, drawbacks, and potential opportunities.
The matching and fusion of data coming from different sensors, as the emissions registered at visible and infrared bands, represents a special challenge, because it has been showed that theses signals are weak correlated. Therefore, many traditional techniques of image processing and computer vision are not helpful, requiring adjustments for their correct performance in every modality.
In this research an experimental study that compares different cost functions and matching approaches is performed, in order to build a multimodal stereovision system. Furthermore, the common problems in infrared/visible stereo, specially in the outdoor scenes are identified. Our framework summarizes the architecture of a generic stereo algorithm, at different levels: computational, functional, and structural, which can be extended toward high-level fusion (semantic) and high-order (prior).The proposed framework is intended to explore novel multimodal stereo matching approaches, going from sparse to dense representations (both disparity and depth maps). Moreover, context information is added in form of priors and assumptions. Finally, this dissertation shows a promissory way toward the integration of multiple sensors for recovering three-dimensional information. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Felipe Lumbreras;Angel Sappa |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ Bar2012 |
Serial |
2209 |
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Author |
Jordi Gonzalez; Thomas B. Moeslund; Liang Wang |
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Title |
Semantic Understanding of Human Behaviors in Image Sequences: From video-surveillance to video-hermeneutics |
Type |
Journal Article |
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Year |
2012 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
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Volume |
116 |
Issue |
3 |
Pages |
305–306 |
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Abstract |
Purpose: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.Methods: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.Results: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.Conclusions: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. |
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ISSN |
1077-3142 |
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Notes |
ISE |
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no |
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Call Number |
Admin @ si @ GMW2012 |
Serial |
2005 |
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Author |
Michal Drozdzal; Petia Radeva; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
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Title |
System and method for automatic detection of in vivo contraction video sequences |
Type |
Patent |
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Year |
2012 |
Publication |
US20120057766 |
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Abstract |
Publication date: 2012/3/8 |
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Notes |
MILAB; OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ DRS2012b |
Serial |
2071 |
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Author |
Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera |
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Title |
Automatic Human Behavior Analysis in ADHD |
Type |
Conference Article |
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Year |
2012 |
Publication |
Eunethydis 2nd International ADHD Conference |
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Poster |
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EUNETHYDIS |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ EMI2012a |
Serial |
2058 |
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Author |
Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera |
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Title |
Análisis Comportamental Automatizado de TDAH: la Influencia de la Variable Motivación |
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Conference Article |
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2012 |
Publication |
IPSI – Cosmocaixa, Jornadas "Empremtes del present, efectes en la psicoanàlisi, la cultura i la societat |
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IPSI |
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Notes |
MILAB; HuPBA; OR |
Approved |
no |
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Call Number |
Admin @ si @ EMI2012b |
Serial |
2065 |
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Author |
Ekaterina Zaytseva; Jordi Vitria |
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Title |
A search based approach to non maximum suppression in face detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
19th IEEE International Conference on Image Processing |
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Poster
paper TA.P5.12
Face detectors typically produce a large number of false positives and this leads to the need to have a further non maximum suppression stage to eliminate multiple and spurious responses. This stage is based on considering spatial heuristics: true positive responses are selected by implicitly considering several restrictions on the spatial distribution of detector responses in natural images. In this paper we analyze the limitations of this approach and propose an efficient search method to overcome them. Results show how the application of this new non-maximum suppression approach to a simple face detector boosts its performance to state of the art results. |
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Orlando; USA; September 2012 |
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ISSN |
1522-4880 |
ISBN |
978-1-4673-2534-9 |
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ICIP |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ ZaV2012 |
Serial |
2060 |
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Author |
Laura Igual; Joan Carles Soliva; Roger Gimeno; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
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Title |
Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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7325 |
Issue |
II |
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222-229 |
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Abstract |
Poster
Studies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation. |
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Aveiro, Portugal |
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LNCS |
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0302-9743 |
ISBN |
978-3-642-31297-7 |
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ICIAR |
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Notes |
OR; HuPBA; MILAB |
Approved |
no |
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Call Number |
Admin @ si @ ISG2012 |
Serial |
2059 |
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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 |
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7378 |
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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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Springer Heidelberg |
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Editor |
F.J. Perales; R.B. Fisher; T.B. Moeslund |
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0302-9743 |
ISBN |
978-3-642-31566-4 |
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AMDO |
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Notes |
MILAB; HuPBA |
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no |
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Call Number |
Admin @ si @ Esc2012 |
Serial |
2040 |
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Author |
Simone Balocco; Carlo Gatta; Marina Alberti; Xavier Carrillo; Juan Rigla; Petia Radeva |
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Title |
Relation between plaque type, plaque thickness, blood shear stress and plaque stress in coronary arteries assessed by X-ray Angiography and Intravascular Ultrasound |
Type |
Journal Article |
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Year |
2012 |
Publication |
Medical Physics |
Abbreviated Journal |
MEDPHYS |
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Volume |
39 |
Issue |
12 |
Pages |
7430-7445 |
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Abstract |
PMID 23231293
PURPOSE:
Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.
METHODS:
First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.
RESULTS:
The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.
CONCLUSIONS:
Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. |
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MILAB |
Approved |
no |
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Call Number |
Admin @ si @BGA2012 |
Serial |
2170 |
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Permanent link to this record |
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Author |
Jaume Gibert |
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Title |
Vector Space Embedding of Graphs via Statistics of Labelling Information |
Type |
Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Pattern recognition is the task that aims at distinguishing objects among different classes. When such a task wants to be solved in an automatic way a crucial step is how to formally represent such patterns to the computer. Based on the different representational formalisms, we may distinguish between statistical and structural pattern recognition. The former describes objects as a set of measurements arranged in the form of what is called a feature vector. The latter assumes that relations between parts of the underlying objects need to be explicitly represented and thus it uses relational structures such as graphs for encoding their inherent information. Vector spaces are a very flexible mathematical structure that has allowed to come up with several efficient ways for the analysis of patterns under the form of feature vectors. Nevertheless, such a representation cannot explicitly cope with binary relations between parts of the objects and it is restricted to measure the exact same number of features for each pattern under study regardless of their complexity. Graph-based representations present the contrary situation. They can easily adapt to the inherent complexity of the patterns but introduce a problem of high computational complexity, hindering the design of efficient tools to process and analyse patterns.
Solving this paradox is the main goal of this thesis. The ideal situation for solving pattern recognition problems would be to represent the patterns using relational structures such as graphs, and to be able to use the wealthy repository of data processing tools from the statistical pattern recognition domain. An elegant solution to this problem is to transform the graph domain into a vector domain where any processing algorithm can be applied. In other words, by mapping each graph to a point in a vector space we automatically get access to the rich set of algorithms from the statistical domain to be applied in the graph domain. Such methodology is called graph embedding.
In this thesis we propose to associate feature vectors to graphs in a simple and very efficient way by just putting attention on the labelling information that graphs store. In particular, we count frequencies of node labels and of edges between labels. Although their locality, these features are able to robustly represent structurally global properties of graphs, when considered together in the form of a vector. We initially deal with the case of discrete attributed graphs, where features are easy to compute. The continuous case is tackled as a natural generalization of the discrete one, where rather than counting node and edge labelling instances, we count statistics of some representatives of them. We encounter how the proposed vectorial representations of graphs suffer from high dimensionality and correlation among components and we face these problems by feature selection algorithms. We also explore how the diversity of different embedding representations can be exploited in order to boost the performance of base classifiers in a multiple classifier systems framework. An extensive experimental evaluation finally shows how the methodology we propose can be efficiently computed and compete with other graph matching and embedding methodologies. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Ernest Valveny |
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DAG |
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Admin @ si @ Gib2012 |
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2204 |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
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Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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7324 |
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I |
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184-191 |
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Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Aveiro, Portugal |
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Springer-Verlag Berlin Heidelberg |
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english |
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Campilho, Aurélio and Kamel, Mohamed |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-31294-6 |
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ICIAR |
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IAM |
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IAM @ iam @ MGH2012a |
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1899 |
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Author |
Naveen Onkarappa; Sujay M. Veerabhadrappa; Angel Sappa |
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Title |
Optical Flow in Onboard Applications: A Study on the Relationship Between Accuracy and Scene Texture |
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Conference Article |
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2012 |
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4th International Conference on Signal and Image Processing |
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221 |
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257-267 |
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Optical flow has got a major role in making advanced driver assistance systems (ADAS) a reality. ADAS applications are expected to perform efficiently in all kinds of environments, those are highly probable, that one can drive the vehicle in different kinds of roads, times and seasons. In this work, we study the relationship of optical flow with different roads, that is by analyzing optical flow accuracy on different road textures. Texture measures such as TeX , TeX and TeX are evaluated for this purpose. Further, the relation of regularization weight to the flow accuracy in the presence of different textures is also analyzed. Additionally, we present a framework to generate synthetic sequences of different textures in ADAS scenarios with ground-truth optical flow. |
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Coimbatore, India |
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1876-1100 |
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978-81-322-0996-6 |
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ADAS |
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Admin @ si @ OVS2012 |
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2356 |
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