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Author |
Jose Manuel Alvarez |
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Title |
Combining Context and Appearance for Road Detection |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the
development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit
color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene.
In this way, we present two different approaches to infer the geometry of the road ahead
the moving vehicle. Finally, we focus on combining these context and appearance (color)
approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art. |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Antonio Lopez;Theo Gevers |
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978-84-937261-8-8 |
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ADAS |
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no |
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Call Number |
Admin @ si @ Alv2010 |
Serial |
1454 |
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Author |
Angel Sappa (ed) |
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Title |
Computer Graphics and Imaging |
Type |
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Year |
2010 |
Publication |
Computer Graphics and Imaging |
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Angel Sappa |
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978–0–88986–836–6 |
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CGIM |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ Sap2010 |
Serial |
1468 |
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Author |
Aura Hernandez-Sabate; Debora Gil |
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Title |
The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries |
Type |
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Year |
2012 |
Publication |
Intravascular Ultrasound |
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Pages |
185-206 |
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Publisher |
Intech |
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Editor |
Yasuhiro Honda |
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Language |
English |
Summary Language |
english |
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978-953-307-900-4 |
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Notes |
IAM; ADAS |
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no |
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Call Number |
IAM @ iam @ HeG2012 |
Serial |
1684 |
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Author |
Ferran Diego |
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Title |
Probabilistic Alignment of Video Sequences Recorded by Moving Cameras |
Type |
Book Whole |
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Year |
2011 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Video alignment consists of integrating multiple video sequences recorded independently into a single video sequence. This means to register both in time (synchronize
frames) and space (image registration) so that the two videos sequences can be fused
or compared pixel–wise. In spite of being relatively unknown, many applications today may benefit from the availability of robust and efficient video alignment methods.
For instance, video surveillance requires to integrate video sequences that are recorded
of the same scene at different times in order to detect changes. The problem of aligning videos has been addressed before, but in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, most works rely
on restrictive assumptions which reduce its difficulty such as linear time correspondence or the knowledge of the complete trajectories of corresponding scene points on the images; to some extent, these assumptions limit the practical applicability of the solutions developed until now. In this thesis, we focus on the challenging problem of aligning sequences recorded at different times from independent moving cameras following similar but not coincident trajectories. More precisely, this thesis covers four studies that advance the state-of-the-art in video alignment. First, we focus on analyzing and developing a probabilistic framework for video alignment, that is, a principled way to integrate multiple observations and prior information. In this way, two different approaches are presented to exploit the combination of several purely visual features (image–intensities, visual words and dense motion field descriptor), and
global positioning system (GPS) information. Second, we focus on reformulating the
problem into a single alignment framework since previous works on video alignment
adopt a divide–and–conquer strategy, i.e., first solve the synchronization, and then
register corresponding frames. This also generalizes the ’classic’ case of fixed geometric transform and linear time mapping. Third, we focus on exploiting directly the
time domain of the video sequences in order to avoid exhaustive cross–frame search.
This provides relevant information used for learning the temporal mapping between
pairs of video sequences. Finally, we focus on adapting these methods to the on–line
setting for road detection and vehicle geolocation. The qualitative and quantitative
results presented in this thesis on a variety of real–world pairs of video sequences show that the proposed method is: robust to varying imaging conditions, different image
content (e.g., incoming and outgoing vehicles), variations on camera velocity, and
different scenarios (indoor and outdoor) going beyond the state–of–the–art. Moreover, the on–line video alignment has been successfully applied for road detection and
vehicle geolocation achieving promising results. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Joan Serrat |
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ADAS |
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no |
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Call Number |
Admin @ si @ Die2011 |
Serial |
1787 |
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Author |
Muhammad Anwer Rao |
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Title |
Color for Object Detection and Action Recognition |
Type |
Book Whole |
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Year |
2013 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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Abstract |
Recognizing object categories in real world images is a challenging problem in computer vision. The deformable part based framework is currently the most successful approach for object detection. Generally, HOG are used for image representation within the part-based framework. For action recognition, the bag-of-word framework has shown to provide promising results. Within the bag-of-words framework, local image patches are described by SIFT descriptor. Contrary to object detection and action recognition, combining color and shape has shown to provide the best performance for object and scene recognition.
In the first part of this thesis, we analyze the problem of person detection in still images. Standard person detection approaches rely on intensity based features for image representation while ignoring the color. Channel based descriptors is one of the most commonly used approaches in object recognition. This inspires us to evaluate incorporating color information using the channel based fusion approach for the task of person detection.
In the second part of the thesis, we investigate the problem of object detection in still images. Due to high dimensionality, channel based fusion increases the computational cost. Moreover, channel based fusion has been found to obtain inferior results for object category where one of the visual varies significantly. On the other hand, late fusion is known to provide improved results for a wide range of object categories. A consequence of late fusion strategy is the need of a pure color descriptor. Therefore, we propose to use Color attributes as an explicit color representation for object detection. Color attributes are compact and computationally efficient. Consequently color attributes are combined with traditional shape features providing excellent results for object detection task.
Finally, we focus on the problem of action detection and classification in still images. We investigate the potential of color for action classification and detection in still images. We also evaluate different fusion approaches for combining color and shape information for action recognition. Additionally, an analysis is performed to validate the contribution of color for action recognition. Our results clearly demonstrate that combining color and shape information significantly improve the performance of both action classification and detection in still images. |
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Address |
Barcelona |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Antonio Lopez;Joost Van de Weijer |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Rao2013 |
Serial |
2281 |
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Author |
Javier Marin |
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Title |
Pedestrian Detection Based on Local Experts |
Type |
Book Whole |
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Year |
2013 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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During the last decade vision-based human detection systems have started to play a key rolein multiple applications linked to driver assistance, surveillance, robot sensing and home automation.
Detecting humans is by far one of the most challenging tasks in Computer Vision.
This is mainly due to the high degree of variability in the human appearanceassociated to
the clothing, pose, shape and size. Besides, other factors such as cluttered scenarios, partial occlusions, or environmental conditions can make the detection task even harder.
Most promising methods of the state-of-the-art rely on discriminative learning paradigms which are fed with positive and negative examples. The training data is one of the most
relevant elements in order to build a robust detector as it has to cope the large variability of the target. In order to create this dataset human supervision is required. The drawback at this point is the arduous effort of annotating as well as looking for such claimed variability.
In this PhD thesis we address two recurrent problems in the literature. In the first stage,we aim to reduce the consuming task of annotating, namely, by using computer graphics.
More concretely, we develop a virtual urban scenario for later generating a pedestrian dataset.
Then, we train a detector using this dataset, and finally we assess if this detector can be successfully applied in a real scenario.
In the second stage, we focus on increasing the robustness of our pedestrian detectors
under partial occlusions. In particular, we present a novel occlusion handling approach to increase the performance of block-based holistic methods under partial occlusions. For this purpose, we make use of local experts via a RandomSubspaceMethod (RSM) to handle these cases. If the method infers a possible partial occlusion, then the RSM, based on performance statistics obtained from partially occluded data, is applied. The last objective of this thesis
is to propose a robust pedestrian detector based on an ensemble of local experts. To achieve this goal, we use the random forest paradigm, where the trees act as ensembles an their nodesare the local experts. In particular, each expert focus on performing a robust classification ofa pedestrian body patch. This approach offers computational efficiency and far less design complexity when compared to other state-of-the-artmethods, while reaching better accuracy |
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Address |
Barcelona |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Antonio Lopez;Jaume Amores |
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ADAS |
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no |
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Call Number |
Admin @ si @ Mar2013 |
Serial |
2280 |
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Author |
Angel Sappa; George A. Triantafyllid |
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Title |
Computer Graphics and Imaging |
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Year |
2012 |
Publication |
Computer Graphics and Imaging |
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Address |
Crete, Greece |
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978-0-88986-921-9 |
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ADAS |
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no |
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Call Number |
Admin @ si @ Sap2012 |
Serial |
2067 |
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Author |
Cristhian Aguilera; M.Ramos; Angel Sappa |
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Title |
Simulated Annealing: A Novel Application of Image Processing in the Wood Area |
Type |
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Year |
2012 |
Publication |
Simulated Annealing – Advances, Applications and Hybridizations |
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Pages |
91-104 |
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Editor |
Marcos de Sales Guerra Tsuzuki |
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978-953-51-0710-1 |
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ADAS |
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no |
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Call Number |
Admin @ si @ ARS2012 |
Serial |
2156 |
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Author |
Angel Sappa; Jordi Vitria |
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Title |
Multimodal Interaction in Image and Video Applications |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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Abstract |
Book Series Intelligent Systems Reference Library |
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Springer Berlin Heidelberg |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Notes |
ADAS; OR;MV |
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no |
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Call Number |
Admin @ si @ SaV2013 |
Serial |
2199 |
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Author |
Mohammad Rouhani |
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Title |
Shape Representation and Registration using Implicit Functions |
Type |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Shape representation and registration are two important problems in computer vision and graphics. Representing the given cloud of points through an implicit function provides a higher level information describing the data. This representation can be more compact more robust to noise and outliers, hence it can be exploited in different computer vision application. In the first part of this thesis implicit shape representations, including both implicit B-spline and polynomial, are tackled. First, an approximation of a geometric distance is proposed to measure the closeness of the given cloud of points and the implicit surface. The analysis of the proposed distance shows an accurate estimation with smooth behavior. The distance by itself is used in a RANSAC based quadratic fitting method. Moreover, since the gradient information of the distance with respect to the surface parameters can be analytically computed, it is used in Levenberg-Marquadt algorithm to refine the surface parameters. In a different approach, an algebraic fitting method is used to represent an object through implicit B-splines. The outcome is a smooth flexible surface and can be represented in different levels from coarse to fine. This property has been exploited to solve the registration problem in the second part of the thesis. In the proposed registration technique the model set is replaced with an implicit representation provided in the first part; then, the point-to-point registration is converted to a point-to-model one in a higher level. This registration error can benefit from different distance estimations to speed up the registration process even without need of correspondence search. Finally, the non-rigid registration problem is tackled through a quadratic distance approximation that is based on the curvature information of the model set. This approximation is used in a free form deformation model to update its control lattice. Then it is shown how an accurate distance approximation can benefit non-rigid registration problems. |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Angel Sappa |
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ADAS |
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Call Number |
Admin @ si @ Rou2012 |
Serial |
2205 |
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