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Author | Ekain Artola | ||||
Title | Human Attention Map Prediction Combining Visual Features | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 160 | Issue | Pages | ||
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Corporate Author | Thesis | Bachelor's thesis | |||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Art2010 | Serial | 1352 | ||
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Author | Marc Serra | ||||
Title | Estimating Intrinsic Images from Physical and Categorical Color Cues | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 151 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ Ser2010 | Serial | 1345 | ||
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Author | Ahmed Mounir Gad | ||||
Title | Object Localization Enhancement by Multiple Segmentation Fusion | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 152 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Mou2010 | Serial | 1346 | ||
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Author | Antonio Hernandez | ||||
Title | Pose and Face Recovery via Spatio-temporal GrabCut Human Segmentation | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 153 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ Her2010 | Serial | 1347 | ||
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Author | Anjan Dutta | ||||
Title | Symbol Spotting in Graphical Documents by Serialized Subgraph Matching | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 159 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ Dut2010 | Serial | 1351 | ||
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Author | David Fernandez | ||||
Title | Handwritten Word Spotting in Old Manuscript Images using Shape Descriptors | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 161 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ Fer2010b | Serial | 1353 | ||
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Author | Jon Almazan | ||||
Title | Deforming the Blurred Shape Model for Shape Description and Recognition | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 163 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Alm2010 | Serial | 1354 | ||
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Author | Nataliya Shapovalova | ||||
Title | On Importance of Interaction and Context | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 155 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Area | Expedition | Conference | |||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ Sha2010 | Serial | 1355 | ||
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Author | Zhanwu Xiong | ||||
Title | A Pompd Model for Active Camera Control | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 156 | Issue | Pages | ||
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Corporate Author | Thesis | Master's thesis | |||
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Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ Xio2010 | Serial | 1356 | ||
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Author | Patricia Marquez | ||||
Title | Conditions Ensuring Accuracy of Local Optical Flow Schemes | Type | Report | ||
Year | 2010 | Publication | CVC Tehcnical Report | Abbreviated Journal | |
Volume | 157 | Issue | Pages | ||
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Abstract | Accurate computation of optical flow is a key-point in many image processing fields. Detection of anomalous and unpredicted agents (such as pedestrians, bikers or cars) in urban scenes or pathology discrimination in medical imaging sequences, to mention just a two. The above kinds sequences present two main difficulties for standard optical flow techniques. On one hand, variability in acquisition conditions (illuminance, medical imaging modality, ...) force an alterantive representation for images fulfilling the britghtness constancy constrain. On the hand, current variational schemes produce oversmoothed fields unable to properly model discontinuous behaviours such as collisions or functionless pathological areas. This master project explores the abilities and limitations of local and global optical flow approaches. The master student will put especial emphasis in the theoretical grounds behind in order to design a variational framework combining the theoretical advantages of the considered techniques. In particular an optical flow based on Gabor phase tracking (developed in the group for medical imaging) will be generalized to urban scenes. | ||||
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Corporate Author | Thesis | Master's thesis | |||
Publisher | Place of Publication | Bellaterra 08193, Barcelona, Spain | Editor | ||
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Notes | IAM; | Approved | no | ||
Call Number | IAM @ iam @ Mar2010 | Serial | 1582 | ||
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Author | Sergio Vera | ||||
Title | Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 164 | Issue | Pages | ||
Keywords | Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score | ||||
Abstract | Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research. | ||||
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Corporate Author | Thesis | Master's thesis | |||
Publisher | Place of Publication | Bellaterra 01893, Barcelona, Spain | Editor | ||
Language | Summary Language | Original Title | |||
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Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ Ver2010 | Serial | 1661 | ||
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Author | Monica Piñol | ||||
Title | Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 162 | Issue | Pages | ||
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Address | Bellaterra (Barcelona) | ||||
Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Piñ2010 | Serial | 1936 | ||
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Author | David Geronimo | ||||
Title | A Global Approach to Vision-Based Pedestrian Detection for Advanced Driver Assistance Systems | Type | Book Whole | ||
Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | At the beginning of the 21th century, traffic accidents have become a major problem not only for developed countries but also for emerging ones. As in other scientific areas in which Artificial Intelligence is becoming a key actor, advanced driver assistance systems, and concretely pedestrian protection systems based on Computer Vision, are becoming a strong topic of research aimed at improving the safety of pedestrians. However, the challenge is of considerable complexity due to the varying appearance of humans (e.g., clothes, size, aspect ratio, shape, etc.), the dynamic nature of on-board systems and the unstructured moving environments that urban scenarios represent. In addition, the required performance is demanding both in terms of computational time and detection rates. In this thesis, instead of focusing on improving specific tasks as it is frequent in the literature, we present a global approach to the problem. Such a global overview starts by the proposal of a generic architecture to be used as a framework both to review the literature and to organize the studied techniques along the thesis. We then focus the research on tasks such as foreground segmentation, object classification and refinement following a general viewpoint and exploring aspects that are not usually analyzed. In order to perform the experiments, we also present a novel pedestrian dataset that consists of three subsets, each one addressed to the evaluation of a different specific task in the system. The results presented in this thesis not only end with a proposal of a pedestrian detection system but also go one step beyond by pointing out new insights, formalizing existing and proposed algorithms, introducing new techniques and evaluating their performance, which we hope will provide new foundations for future research in the area. | ||||
Address | Antonio Lopez;Krystian Mikolajczyk;Jaume Amores;Dariu M. Gavrila;Oriol Pujol;Felipe Lumbreras | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Krystian Mikolajczyk;Jaume Amores;Dariu M. Gavrila;Oriol Pujol;Felipe Lumbreras | |
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-84-936529-5-1 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ Ger2010 | Serial | 1279 | ||
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Author | Ignasi Rius | ||||
Title | Motion Priors for Efficient Bayesian Tracking in Human Sequence Evaluation | Type | Book Whole | ||
Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | Recovering human motion by visual analysis is a challenging computer vision research
area with a lot of potential applications. Model-based tracking approaches, and in particular particle lters, formulate the problem as a Bayesian inference task whose aim is to sequentially estimate the distribution of the parameters of a human body model over time. These approaches strongly rely on good dynamical and observation models to predict and update congurations of the human body according to measurements from the image data. However, it is very dicult to design observation models which extract useful and reliable information from image sequences robustly. This results specially challenging in monocular tracking given that only one viewpoint from the scene is available. Therefore, to overcome these limitations strong motion priors are needed to guide the exploration of the state space. The work presented in this Thesis is aimed to retrieve the 3D motion parameters of a human body model from incomplete and noisy measurements of a monocular image sequence. These measurements consist of the 2D positions of a reduced set of joints in the image plane. Towards this end, we present a novel action-specic model of human motion which is trained from several databases of real motion-captured performances of an action, and is used as a priori knowledge within a particle ltering scheme. Body postures are represented by means of a simple and compact stick gure model which uses direction cosines to represent the direction of body limbs in the 3D Cartesian space. Then, for a given action, Principal Component Analysis is applied to the training data to perform dimensionality reduction over the highly correlated input data. Before the learning stage of the action model, the input motion performances are synchronized by means of a novel dense matching algorithm based on Dynamic Programming. The algorithm synchronizes all the motion sequences of the same action class, nding an optimal solution in real-time. Then, a probabilistic action model is learnt, based on the synchronized motion examples, which captures the variability and temporal evolution of full-body motion within a specic action. In particular, for each action, the parameters learnt are: a representative manifold for the action consisting of its mean performance, the standard deviation from the mean performance, the mean observed direction vectors from each motion subsequence of a given length and the expected error at a given time instant. Subsequently, the action-specic model is used as a priori knowledge on human motion which improves the eciency and robustness of the overall particle filtering tracking framework. First, the dynamic model guides the particles according to similar situations previously learnt. Then, the state space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, the state space is explored more eciently as the particle set covers the most probable body postures. Finally, experiments are carried out using test sequences from several motion databases. Results point out that our tracker scheme is able to estimate the rough 3D conguration of a full-body model providing only the 2D positions of a reduced set of joints. Separate tests on the sequence synchronization method and the subsequence probabilistic matching technique are also provided. |
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-84-937261-9-5 | Medium | ||
Area | Expedition | Conference | |||
Notes | Approved | no | |||
Call Number | Admin @ si @ Riu2010 | Serial | 1331 | ||
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Author | Ivan Huerta | ||||
Title | Foreground Object Segmentation and Shadow Detection for Video Sequences in Uncontrolled Environments | Type | Book Whole | ||
Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | This Thesis is mainly divided in two parts. The first one presents a study of motion
segmentation problems. Based on this study, a novel algorithm for mobile-object segmentation from a static background scene is also presented. This approach is demonstrated robust and accurate under most of the common problems in motion segmentation. The second one tackles the problem of shadows in depth. Firstly, a bottom-up approach based on a chromatic shadow detector is presented to deal with umbra shadows. Secondly, a top-down approach based on a tracking system has been developed in order to enhance the chromatic shadow detection. In our first contribution, a case analysis of motion segmentation problems is presented by taking into account the problems associated with different cues, namely colour, edge and intensity. Our second contribution is a hybrid architecture which handles the main problems observed in such a case analysis, by fusing (i) the knowledge from these three cues and (ii) a temporal difference algorithm. On the one hand, we enhance the colour and edge models to solve both global/local illumination changes (shadows and highlights) and camouflage in intensity. In addition, local information is exploited to cope with a very challenging problem such as the camouflage in chroma. On the other hand, the intensity cue is also applied when colour and edge cues are not available, such as when beyond the dynamic range. Additionally, temporal difference is included to segment motion when these three cues are not available, such as that background not visible during the training period. Lastly, the approach is enhanced for allowing ghost detection. As a result, our approach obtains very accurate and robust motion segmentation in both indoor and outdoor scenarios, as quantitatively and qualitatively demonstrated in the experimental results, by comparing our approach with most best-known state-of-the-art approaches. Motion Segmentation has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. Firstly, a bottom-up approach for detection and removal of chromatic moving shadows in surveillance scenarios is proposed. Secondly, a top-down approach based on kalman filters to detect and track shadows has been developed in order to enhance the chromatic shadow detection. In the Bottom-up part, the shadow detection approach applies a novel technique based on gradient and colour models for separating chromatic moving shadows from moving objects. Well-known colour and gradient models are extended and improved into an invariant colour cone model and an invariant gradient model, respectively, to perform automatic segmentation while detecting potential shadows. Hereafter, the regions corresponding to potential shadows are grouped by considering ”a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between local gradient structures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. In the top-down process, after detection of objects and shadows both are tracked using Kalman filters, in order to enhance the chromatic shadow detection, when it fails to detect a shadow. Firstly, this implies a data association between the blobs (foreground and shadow) and Kalman filters. Secondly, an event analysis of the different data association cases is performed, and occlusion handling is managed by a Probabilistic Appearance Model (PAM). Based on this association, temporal consistency is looked for the association between foregrounds and shadows and their respective Kalman Filters. From this association several cases are studied, as a result lost chromatic shadows are correctly detected. Finally, the tracking results are used as feedback to improve the shadow and object detection. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. |
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-84-937261-3-3 | Medium | ||
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Notes | Approved | no | |||
Call Number | ISE @ ise @ Hue2010 | Serial | 1332 | ||
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