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Author | Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers | ||||
Title | Adapting Pedestrian Detection from Synthetic to Far Infrared Images | Type | Conference Article | ||
Year | 2013 | Publication | ICCV Workshop on Visual Domain Adaptation and Dataset Bias | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Domain Adaptation; Far Infrared; Pedestrian Detection | ||||
Abstract | We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. | ||||
Address | Sydney; Australia; December 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Sydney, Australy | Editor | ||
Language | English | Summary Language | Original Title | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICCVW-VisDA | ||
Notes | ADAS; 600.054; 600.055; 600.057; 601.217;ISE | Approved | no | ||
Call Number | ADAS @ adas @ SRV2013 | Serial | 2334 | ||
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Author | V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta | ||||
Title | The ICDAR/GREC 2013 Music Scores Competition on Staff Removal | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Competition; Music scores; Staff Removal | ||||
Abstract | The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. | ||||
Address | Bethlehem; PA; USA; August 2013 | ||||
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 | GREC | ||
Notes | DAG; 600.045; 600.061 | Approved | no | ||
Call Number | Admin @ si @ KFV2013 | Serial | 2337 | ||
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Author | Jorge Bernal; David Vazquez (eds) | ||||
Title | Computer vision Trends and Challenges | Type | Book Whole | ||
Year | 2013 | Publication | Computer vision Trends and Challenges | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | CVCRD; Computer Vision | ||||
Abstract | This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community. We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | Jorge Bernal; David Vazquez | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-84-940902-2-6 | Medium | ||
Area | Expedition | Conference | |||
Notes | Approved | no | |||
Call Number | ADAS @ adas @ BeV2013 | Serial | 2339 | ||
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Author | Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados | ||||
Title | Classification of Administrative Document Images by Logo Identification | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. | ||||
Address | Bethlehem; PA; USA; August 2013 | ||||
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 | GREC | ||
Notes | DAG; 600.056; 600.045; 605.203 | Approved | no | ||
Call Number | Admin @ si @ | Serial | 2348 | ||
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Author | Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados | ||||
Title | Spotting Graphical Symbols in Camera-Acquired Documents in Real Time | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. | ||||
Address | Bethlehem; PA; USA; August 2013 | ||||
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 | GREC | ||
Notes | DAG; 600.045; 600.055; 600.061; 602.101 | Approved | no | ||
Call Number | Admin @ si @ RKL2013 | Serial | 2347 | ||
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Author | Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez | ||||
Title | Multi-task Bilinear Classifiers for Visual Domain Adaptation | Type | Conference Article | ||
Year | 2013 | Publication | Advances in Neural Information Processing Systems Workshop | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Domain Adaptation; Pedestrian Detection; ADAS | ||||
Abstract | We propose a method that aims to lessen the significant accuracy degradation
that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation. The bilinear classifier encodes the feature transformation and classification parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines. |
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Address | Lake Tahoe; Nevada; USA; December 2013 | ||||
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 | NIPSW | ||
Notes | ADAS; 600.054; 600.057; 601.217;ISE | Approved | no | ||
Call Number | ADAS @ adas @ XRH2013 | Serial | 2340 | ||
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Author | Alvaro Cepero; Albert Clapes; Sergio Escalera | ||||
Title | Quantitative analysis of non-verbal communication for competence analysis | Type | Conference Article | ||
Year | 2013 | Publication | 16th Catalan Conference on Artificial Intelligence | Abbreviated Journal | |
Volume | 256 | Issue | Pages | 105-114 | |
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Abstract | |||||
Address | Vic; October 2013 | ||||
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 | CCIA | ||
Notes | HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ CCE2013 | Serial | 2324 | ||
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Author | Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez;Josep Llados | ||||
Title | Perceptual retrieval of architectural floor plans | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | This paper proposes a runlength histogram signature as a percetual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query,
similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Preliminary results show the interest of the proposed approach and opens a challenging research line in graphics recognition. |
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Address | Bethlehem; PA; USA; August 2013 | ||||
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 | GREC | ||
Notes | DAG; 600.045; 600.056; 600.061 | Approved | no | ||
Call Number | Admin @ si @ HFF2013a | Serial | 2320 | ||
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Author | Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez | ||||
Title | Combining structural and statistical strategies for unsupervised wall detection in floor plans | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | This paper presents an evolution of the first unsupervised wall segmentation method in floor plans, that was presented by the authors in [1]. This first approach, contrarily to the existing ones, is able to segment walls independently to their notation and without the need of any pre-annotated data
to learn their visual appearance. Despite the good performance of the first approach, some specific cases, such as curved shaped walls, were not correctly segmented since they do not agree the strict structural assumptions that guide the whole methodology in order to be able to learn, in an unsupervised way, the structure of a wall. In this paper, we refine this strategy by dividing the process in two steps. In a first step, potential wall segments are extracted unsupervisedly using a modification of [1], by restricting even more the areas considered as walls in a first moment. In a second step, these segments are used to learn and spot lost instances based on a modified version of [2], also presented by the authors. The presented combined method have been tested on 4 datasets with different notations and compared with the stateof-the-art applyed on the same datasets. The results show its adaptability to different wall notations and shapes, significantly outperforming the original approach. |
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Address | Bethlehem; PA; USA; August 2013 | ||||
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 | GREC | ||
Notes | DAG; 600.045 | Approved | no | ||
Call Number | Admin @ si @ HVS2013a | Serial | 2321 | ||
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Author | Enric Marti; Ferran Poveda; Antoni Gurgui; Jaume Rocarias; Debora Gil | ||||
Title | Una propuesta de seguimiento, tutorías on line y evaluación en la metodología de Aprendizaje Basado en Proyectos | Type | Miscellaneous | ||
Year | 2013 | Publication | IV Congreso Internacional UNIVEST | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Poster | ||||
Address | Girona | ||||
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 | UNIVEST | ||
Notes | IAM | Approved | no | ||
Call Number | Admin @ si @ MPG2013a | Serial | 2304 | ||
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Author | Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil | ||||
Title | Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition | Type | Conference Article | ||
Year | 2013 | Publication | 16th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | |||||
Address | Nagoya; Japan; September 2013 | ||||
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 | MICCAI | ||
Notes | IAM | Approved | no | ||
Call Number | Admin @ si @ VGG2013 | Serial | 2301 | ||
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Author | Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados | ||||
Title | An interactive appearance-based document retrieval system for historical newspapers | Type | Conference Article | ||
Year | 2013 | Publication | Proceedings of the International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | Issue | Pages | 84-87 | ||
Keywords | |||||
Abstract | In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers. | ||||
Address | Barcelona; February 2013 | ||||
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 | VISAPP | ||
Notes | DAG; 600.056; 600.045; 605.203 | Approved | no | ||
Call Number | Admin @ si @ GRK2013a | Serial | 2290 | ||
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Author | Muhammad Anwer Rao | ||||
Title | Color for Object Detection and Action Recognition | Type | Book Whole | ||
Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
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 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Joost Van de Weijer | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Rao2013 | Serial | 2281 | ||
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Author | Javier Marin | ||||
Title | Pedestrian Detection Based on Local Experts | Type | Book Whole | ||
Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | 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 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Jaume Amores | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Mar2013 | Serial | 2280 | ||
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Author | Wenjuan Gong | ||||
Title | 3D Motion Data aided Human Action Recognition and Pose Estimation | Type | Book Whole | ||
Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | In this work, we explore human action recognition and pose estimation prob-
lems. Different from traditional works of learning from 2D images or video sequences and their annotated output, we seek to solve the problems with ad- ditional 3D motion capture information, which helps to fill the gap between 2D image features and human interpretations. We first compare two different schools of approaches commonly used for 3D pose estimation from 2D pose configuration: modeling and learning methods. By looking into experiments results and considering our problems, we fixed a learning method as the following approaches to do pose estimation. We then establish a framework by adding a module of detecting 2D pose configuration from images with varied background, which widely extend the application of the approach. We also seek to directly estimate 3D poses from image features, instead of estimating 2D poses as a intermediate module. We explore a robust input feature, which combined with the proposed distance measure, provides a solution for noisy or corrupted inputs. We further utilize the above method to estimate weak poses,which is a concise representation of the original poses by using dimension deduction technologies, from image features. Weak pose space is where we calculate vocabulary and label action types using a bog of words pipeline. Temporal information of an action is taken into consideration by considering several consecutive frames as a single unit for computing vocabulary and histogram assignments. |
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Address | Barcelona | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ Gon2013 | Serial | 2279 | ||
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