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Author | Jaime Moreno; Xavier Otazu | ||||
Title | Image coder based on Hilbert scanning of embedded quadTrees | Type ![]() |
Conference Article | ||
Year | 2011 | Publication | Data Compression Conference | Abbreviated Journal | |
Volume | Issue | Pages | 470-470 | ||
Keywords | |||||
Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DCC | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ MoO2011b | Serial | 2177 | ||
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Author | Bogdan Raducanu; Fadi Dornaika | ||||
Title | Pose-Invariant Face Recognition in Videos for Human-Machine Interaction | Type ![]() |
Conference Article | ||
Year | 2012 | Publication | 12th European Conference on Computer Vision | Abbreviated Journal | |
Volume | 7584 | Issue | Pages | 566.575 | |
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Abstract | Human-machine interaction is a hot topic nowadays in the communities of computer vision and robotics. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, pose, and occlusions. In this paper, we propose a novel approach for robust pose-invariant face recognition for human-robot interaction based on the real-time fitting of a 3D deformable model to input images taken from video sequences. More concrete, our approach generates a rectified face image irrespective with the actual head-pose orientation. Experimental results performed on Honda video database, using several manifold learning techniques, show a distinct advantage of the proposed method over the standard 2D appearance-based snapshot approach. | ||||
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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 | 978-3-642-33867-0 | Medium | |
Area | Expedition | Conference | ECCVW | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ RaD2012e | Serial | 2182 | ||
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Author | Jose Manuel Alvarez; Y. LeCun; Theo Gevers; Antonio Lopez | ||||
Title | Semantic Road Segmentation via Multi-Scale Ensembles of Learned Features | Type ![]() |
Conference Article | ||
Year | 2012 | Publication | 12th European Conference on Computer Vision – Workshops and Demonstrations | Abbreviated Journal | |
Volume | 7584 | Issue | Pages | 586-595 | |
Keywords | road detection | ||||
Abstract | Semantic segmentation refers to the process of assigning an object label (e.g., building, road, sidewalk, car, pedestrian) to every pixel in an image. Common approaches formulate the task as a random field labeling problem modeling the interactions between labels by combining local and contextual features such as color, depth, edges, SIFT or HoG. These models are trained to maximize the likelihood of the correct classification given a training set. However, these approaches rely on hand–designed features (e.g., texture, SIFT or HoG) and a higher computational time required in the inference process.
Therefore, in this paper, we focus on estimating the unary potentials of a conditional random field via ensembles of learned features. We propose an algorithm based on convolutional neural networks to learn local features from training data at different scales and resolutions. Then, diversification between these features is exploited using a weighted linear combination. Experiments on a publicly available database show the effectiveness of the proposed method to perform semantic road scene segmentation in still images. The algorithm outperforms appearance based methods and its performance is similar compared to state–of–the–art methods using other sources of information such as depth, motion or stereo. |
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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 | 978-3-642-33867-0 | Medium | |
Area | Expedition | Conference | ECCVW | ||
Notes | ADAS;ISE | Approved | no | ||
Call Number | Admin @ si @ ALG2012; ADAS @ adas | Serial | 2187 | ||
Permanent link to this record | |||||
Author | Jordi Roca; Maria Vanrell; C. Alejandro Parraga | ||||
Title | What is constant in colour constancy? | Type ![]() |
Conference Article | ||
Year | 2012 | Publication | 6th European Conference on Colour in Graphics, Imaging and Vision | Abbreviated Journal | |
Volume | Issue | Pages | 337-343 | ||
Keywords | |||||
Abstract | Color constancy refers to the ability of the human visual system to stabilize
the color appearance of surfaces under an illuminant change. In this work we studied how the interrelations among nine colors are perceived under illuminant changes, particularly whether they remain stable across 10 different conditions (5 illuminants and 2 backgrounds). To do so we have used a paradigm that measures several colors under an immersive state of adaptation. From our measures we defined a perceptual structure descriptor that is up to 87% stable over all conditions, suggesting that color category features could be used to predict color constancy. This is in agreement with previous results on the stability of border categories [1,2] and with computational color constancy algorithms [3] for estimating the scene illuminant. |
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 9781622767014 | Medium | ||
Area | Expedition | Conference | CGIV | ||
Notes | CIC | Approved | no | ||
Call Number | RVP2012 | Serial | 2189 | ||
Permanent link to this record | |||||
Author | Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool | ||||
Title | Active MAP Inference in CRFs for Efficient Semantic Segmentation | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 2312 - 2319 | ||
Keywords | Semantic Segmentation | ||||
Abstract | Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains. | ||||
Address | Sydney; Australia; 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 | 1550-5499 | ISBN | Medium | ||
Area | Expedition | Conference | ICCV | ||
Notes | ADAS; 600.057 | Approved | no | ||
Call Number | ADAS @ adas @ RBN2013 | Serial | 2377 | ||
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Author | Joan M. Nuñez; Debora Gil; Fernando Vilariño | ||||
Title | Finger joint characterization from X-ray images for rheymatoid arthritis assessment | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | 6th International Conference on Biomedical Electronics and Devices | Abbreviated Journal | |
Volume | Issue | Pages | 288-292 | ||
Keywords | Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde | ||||
Abstract | In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection. | ||||
Address | Barcelona; February 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | SciTePress | 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 | 800 | Expedition | Conference | BIODEVICES | |
Notes | IAM;MV; 600.057; 600.054;SIAI | Approved | no | ||
Call Number | IAM @ iam @ NGV2013 | Serial | 2196 | ||
Permanent link to this record | |||||
Author | Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
Title | Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | Proceedings of the International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 162-171 | |
Keywords | Colonoscopy; Blood vessel; Linear features; Valley detection | ||||
Abstract | This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance. |
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Address | Barcelona; February 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | SciTePress | 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 | 800 | Expedition | Conference | VISIGRAPP | |
Notes | MV; 600.054; 600.057;SIAI | Approved | no | ||
Call Number | IAM @ iam @ NBS2013 | Serial | 2198 | ||
Permanent link to this record | |||||
Author | David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha | ||||
Title | On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts | Type ![]() |
Conference Article | ||
Year | 2012 | Publication | 13th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 763-768 | ||
Keywords | document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding | ||||
Abstract | he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20% | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4673-2262-1 | Medium | ||
Area | Expedition | Conference | ICFHR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ FLF2012 | Serial | 2200 | ||
Permanent link to this record | |||||
Author | Jiaolong Xu; David Vazquez; Antonio Lopez; Javier Marin; Daniel Ponsa | ||||
Title | Learning a Multiview Part-based Model in Virtual World for Pedestrian Detection | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | IEEE Intelligent Vehicles Symposium | Abbreviated Journal | |
Volume | Issue | Pages | 467 - 472 | ||
Keywords | Pedestrian Detection; Virtual World; Part based | ||||
Abstract | State-of-the-art deformable part-based models based on latent SVM have shown excellent results on human detection. In this paper, we propose to train a multiview deformable part-based model with automatically generated part examples from virtual-world data. The method is efficient as: (i) the part detectors are trained with precisely extracted virtual examples, thus no latent learning is needed, (ii) the multiview pedestrian detector enhances the performance of the pedestrian root model, (iii) a top-down approach is used for part detection which reduces the searching space. We evaluate our model on Daimler and Karlsruhe Pedestrian Benchmarks with publicly available Caltech pedestrian detection evaluation framework and the result outperforms the state-of-the-art latent SVM V4.0, on both average miss rate and speed (our detector is ten times faster). | ||||
Address | Gold Coast; Australia; June 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | IEEE | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1931-0587 | ISBN | 978-1-4673-2754-1 | Medium | |
Area | Expedition | Conference | IV | ||
Notes | ADAS; 600.054; 600.057 | Approved | no | ||
Call Number | XVL2013; ADAS @ adas @ xvl2013a | Serial | 2214 | ||
Permanent link to this record | |||||
Author | Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann | ||||
Title | When Is A Confidence Measure Good Enough? | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | 9th International Conference on Computer Vision Systems | Abbreviated Journal | |
Volume | 7963 | Issue | Pages | 344-353 | |
Keywords | Optical flow, confidence measure, performance evaluation | ||||
Abstract | Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions,
thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. |
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Address | St Petersburg; Russia; July 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Link | 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 | 978-3-642-39401-0 | Medium | |
Area | Expedition | Conference | ICVS | ||
Notes | IAM;ADAS; 600.044; 600.057; 600.060; 601.145 | Approved | no | ||
Call Number | IAM @ iam @ MGH2013a | Serial | 2218 | ||
Permanent link to this record | |||||
Author | David Vazquez; Jiaolong Xu; Sebastian Ramos; Antonio Lopez; Daniel Ponsa | ||||
Title | Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | CVPR Workshop on Ground Truth – What is a good dataset? | Abbreviated Journal | |
Volume | Issue | Pages | 706 - 711 | ||
Keywords | Pedestrian Detection; Domain Adaptation | ||||
Abstract | Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem. Accordingly, in this paper we assess an strategy to collect samples from the real world and retrain with them, thus avoiding the dataset shift, but in such a way that no BBs of real-world pedestrians have to be provided. In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required). Then, using such a classifier we collect pedestrian samples from real-world images by detection. After, a human oracle rejects the false detections efficiently (weak annotation). Finally, a new classifier is trained with the accepted detections. We show that this classifier is competitive with respect to the counterpart trained with samples collected by manually annotating hundreds of pedestrian BBs. | ||||
Address | Portland; Oregon; June 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | IEEE | Place of Publication | Editor | ||
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CVPRW | ||
Notes | ADAS; 600.054; 600.057; 601.217 | Approved | no | ||
Call Number | ADAS @ adas @ VXR2013a | Serial | 2219 | ||
Permanent link to this record | |||||
Author | Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa | ||||
Title | Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers | Type ![]() |
Conference Article | ||
Year | 2013 | Publication | CVPR Workshop on Ground Truth – What is a good dataset? | Abbreviated Journal | |
Volume | Issue | Pages | 688 - 693 | ||
Keywords | Pedestrian Detection; Domain Adaptation | ||||
Abstract | Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. | ||||
Address | Portland; oregon; June 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CVPRW | ||
Notes | ADAS; 600.054; 600.057; 601.217 | Approved | yes | ||
Call Number | XVR2013; ADAS @ adas @ xvr2013a | Serial | 2220 | ||
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Author | A. Ruiz; Joost Van de Weijer; Xavier Binefa | ||||
Title | Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization | Type ![]() |
Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | We address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions and how they determine the video weak-labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized Multi-Concept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection. | ||||
Address | Nottingham; UK; September 2014 | ||||
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Area | Expedition | Conference | BMVC | ||
Notes | LAMP; CIC; 600.074; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RWB2014 | Serial | 2508 | ||
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Author | Mirko Arnold; Anarta Ghosh; Gerard Lacey; Stephen Patchett; Hugh Mulcahy | ||||
Title | Indistinct frame detection in colonoscopy videos | Type ![]() |
Conference Article | ||
Year | 2009 | Publication | Machine Vision and Image Processing Conference | Abbreviated Journal | |
Volume | Issue | Pages | 47-52 | ||
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Area | 800 | Expedition | Conference | ||
Notes | MV | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2424 | ||
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Author | Mirko Arnold; Stephan Ameling; Anarta Ghosh; Gerard Lacey | ||||
Title | Quality Improvement of Endoscopy Videos | Type ![]() |
Conference Article | ||
Year | 2011 | Publication | Proceedings of the 8th IASTED International Conference on Biomedical Engineering | Abbreviated Journal | |
Volume | 723 | Issue | Pages | ||
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Area | 800 | Expedition | Conference | ||
Notes | MV | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2426 | ||
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