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Author  |
Diego Cheda; Daniel Ponsa; Antonio Lopez | ||||
| Title | Monocular Depth-based Background Estimation | Type | Conference Article | ||
| Year | 2012 | Publication | 7th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 323-328 | ||
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| Abstract | In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences. | ||||
| Address | Roma | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e | Serial | 2012 | ||
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| Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez | ||||
| Title | Pedestrian Candidates Generation using Monocular Cues | Type | Conference Article | ||
| Year | 2012 | Publication | IEEE Intelligent Vehicles Symposium | Abbreviated Journal | |
| Volume | Issue | Pages | 7-12 | ||
| Keywords | pedestrian detection | ||||
| Abstract | Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached. | ||||
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| Publisher | IEEE Xplore | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1931-0587 | ISBN | 978-1-4673-2119-8 | Medium | |
| Area | Expedition | Conference | IV | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d | Serial | 2013 | ||
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| Author |
Ekaterina Zaytseva; Jordi Vitria | ||||
| Title | A search based approach to non maximum suppression in face detection | Type | Conference Article | ||
| Year | 2012 | Publication | 19th IEEE International Conference on Image Processing | Abbreviated Journal | |
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| Abstract | 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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| Address | Orlando; USA; September 2012 | ||||
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| ISSN | 1522-4880 | ISBN | 978-1-4673-2534-9 | Medium | |
| Area | Expedition | Conference | ICIP | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ ZaV2012 | Serial | 2060 | ||
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| Author |
Ekaterina Zaytseva; Santiago Segui; Jordi Vitria | ||||
| Title | Sketchable Histograms of Oriented Gradients for Object Detection | Type | Conference Article | ||
| Year | 2012 | Publication | 17th Iberomerican Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | 7441 | Issue | Pages | 374-381 | |
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| Abstract | In this paper we investigate a new representation approach for visual object recognition. The new representation, called sketchable-HoG, extends the classical histogram of oriented gradients (HoG) feature by adding two different aspects: the stability of the majority orientation and the continuity of gradient orientations. In this way, the sketchable-HoG locally characterizes the complexity of an object model and introduces global structure information while still keeping simplicity, compactness and robustness. We evaluated the proposed image descriptor on publicly Catltech 101 dataset. The obtained results outperforms classical HoG descriptor as well as other reported descriptors in the literature. | ||||
| Address | Buenos Aires, Argentina | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-33274-6 | Medium | |
| Area | Expedition | Conference | CIARP | ||
| Notes | OR; MILAB;MV | Approved | no | ||
| Call Number | Admin @ si @ ZSV2012 | Serial | 2048 | ||
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| Author |
Emanuel Indermühle; Volkmar Frinken; Horst Bunke | ||||
| Title | Mode Detection in Online Handwritten Documents using BLSTM Neural Networks | Type | Conference Article | ||
| Year | 2012 | Publication | 13th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 302-307 | ||
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| Abstract | Mode detection in online handwritten documents refers to the process of distinguishing different types of contents, such as text, formulas, diagrams, or tables, one from another. In this paper a new approach to mode detection is proposed that uses bidirectional long-short term memory (BLSTM) neural networks. The BLSTM neural network is a novel type of recursive neural network that has been successfully applied in speech and handwriting recognition. In this paper we show that it has the potential to significantly outperform traditional methods for mode detection, which are usually based on stroke classification. As a further advantage over previous approaches, the proposed system is trainable and does not rely on user-defined heuristics. Moreover, it can be easily adapted to new or additional types of modes by just providing the system with new training data. | ||||
| Address | Bari, italy | ||||
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| ISSN | ISBN | 978-1-4673-2262-1 | Medium | ||
| Area | Expedition | Conference | ICFHR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ IFB2012 | Serial | 2056 | ||
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| Author |
Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez | ||||
| Title | Adaptation of a computer programming course to the EXHE requirements: evaluation five years later | Type | Miscellaneous | ||
| Year | 2012 | Publication | European Journal of Engineering Education | Abbreviated Journal | |
| Volume | 37 | Issue | 3 | Pages | 243-254 |
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| Notes | DAG; CIC; OR; invisible;MV | Approved | no | ||
| Call Number | Admin @ si @ VBL2012 | Serial | 2070 | ||
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| Author |
Fadi Dornaika; A.Assoum; Bogdan Raducanu | ||||
| Title | Automatic Dimensionality Estimation for Manifold Learning through Optimal Feature Selection | Type | Conference Article | ||
| Year | 2012 | Publication | Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop | Abbreviated Journal | |
| Volume | 7626 | Issue | Pages | 575-583 | |
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| Abstract | A very important aspect in manifold learning is represented by automatic estimation of the intrinsic dimensionality. Unfortunately, this problem has received few attention in the literature of manifold learning. In this paper, we argue that feature selection paradigm can be used to the problem of automatic dimensionality estimation. Besides this, it also leads to improved recognition rates. Our approach for optimal feature selection is based on a Genetic Algorithm. As a case study for manifold learning, we have considered Laplacian Eigenmaps (LE) and Locally Linear Embedding (LLE). The effectiveness of the proposed framework was tested on the face recognition problem. Extensive experiments carried out on ORL, UMIST, Yale, and Extended Yale face data sets confirmed our hypothesis. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-34165-6 | Medium | |
| Area | Expedition | Conference | SSPR&SPR | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DAR2012 | Serial | 2174 | ||
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| Author |
Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu | ||||
| Title | LSDA Solution Schemes for Modelless 3D Head Pose Estimation | Type | Conference Article | ||
| Year | 2012 | Publication | IEEE Workshop on the Applications of Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 393-398 | ||
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| Address | Breckenridge; USA; | ||||
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| Area | Expedition | Conference | WACV | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DBR2012 | Serial | 1889 | ||
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| Author |
Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation | Type | Book Chapter | ||
| Year | 2012 | Publication | Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions | Abbreviated Journal | |
| Volume | Issue | Pages | 157-178 | ||
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| Publisher | NOVA Publishers | Place of Publication | Editor | S.E. Carter | |
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DoR2012 | Serial | 2183 | ||
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| Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell | ||||
| Title | Modulating Shape Features by Color Attention for Object Recognition | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
| Volume | 98 | Issue | 1 | Pages | 49-64 |
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| Abstract | Bag-of-words based image representation is a successful approach for object recognition. Generally, the subsequent stages of the process: feature detection,feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom up and top-down attention maps. Subsequently, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information. | ||||
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| Publisher | Springer Netherlands | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0920-5691 | ISBN | Medium | ||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ KWV2012 | Serial | 1864 | ||
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| Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez | ||||
| Title | Color Attributes for Object Detection | Type | Conference Article | ||
| Year | 2012 | Publication | 25th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 3306-3313 | ||
| Keywords | pedestrian detection | ||||
| Abstract | State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape. In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe- art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods. |
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| Address | Providence; Rhode Island; USA; | ||||
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| Publisher | IEEE Xplore | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | 978-1-4673-1226-4 | Medium | |
| Area | Expedition | Conference | CVPR | ||
| Notes | ADAS; CIC; | Approved | no | ||
| Call Number | Admin @ si @ KRW2012 | Serial | 1935 | ||
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| Author |
Fernando Barrera | ||||
| Title | Multimodal Stereo from Thermal Infrared and Visible Spectrum | Type | Book Whole | ||
| 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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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Felipe Lumbreras;Angel Sappa | |
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Bar2012 | Serial | 2209 | ||
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| Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
| Title | Evaluation of Similarity Functions in Multimodal Stereo | Type | Conference Article | ||
| Year | 2012 | Publication | 9th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 7324 | Issue | I | Pages | 320-329 |
| Keywords | Aveiro, Portugal | ||||
| Abstract | This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-31294-6 | Medium | |
| Area | Expedition | Conference | ICIAR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | BLS2012a | Serial | 2014 | ||
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| Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
| Title | Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation | Type | Journal Article | ||
| Year | 2012 | Publication | IEEE Journal of Selected Topics in Signal Processing | Abbreviated Journal | J-STSP |
| Volume | 6 | Issue | 5 | Pages | 437-446 |
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| Abstract | This paper proposes an imaging system for computing sparse depth maps from multispectral images. A special stereo head consisting of an infrared and a color camera defines the proposed multimodal acquisition system. The cameras are rigidly attached so that their image planes are parallel. Details about the calibration and image rectification procedure are provided. Sparse disparity maps are obtained by the combined use of mutual information enriched with gradient information. The proposed approach is evaluated using a Receiver Operating Characteristics curve. Furthermore, a multispectral dataset, color and infrared images, together with their corresponding ground truth disparity maps, is generated and used as a test bed. Experimental results in real outdoor scenarios are provided showing its viability and that the proposed approach is not restricted to a specific domain. | ||||
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| ISSN | 1932-4553 | ISBN | Medium | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ BLS2012b | Serial | 2155 | ||
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| Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa | ||||
| Title | Planar-Based Multispectral Stereo | Type | Conference Article | ||
| Year | 2012 | Publication | 11th Quantitative InfraRed Thermography | Abbreviated Journal | |
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| Address | Naples, Italy | ||||
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| Area | Expedition | Conference | QIRT | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ BLA2012 | Serial | 2016 | ||
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