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| Author | Fei Yang; Yaxing Wang; Luis Herranz; Yongmei Cheng; Mikhail Mozerov | ||||
| Title | A Novel Framework for Image-to-image Translation and Image Compression | Type | Journal Article | ||
| Year | 2022 | Publication | Neurocomputing | Abbreviated Journal  |
NEUCOM |
| Volume | 508 | Issue | Pages | 58-70 | |
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| Abstract | Data-driven paradigms using machine learning are becoming ubiquitous in image processing and communications. In particular, image-to-image (I2I) translation is a generic and widely used approach to image processing problems, such as image synthesis, style transfer, and image restoration. At the same time, neural image compression has emerged as a data-driven alternative to traditional coding approaches in visual communications. In this paper, we study the combination of these two paradigms into a joint I2I compression and translation framework, focusing on multi-domain image synthesis. We first propose distributed I2I translation by integrating quantization and entropy coding into an I2I translation framework (i.e. I2Icodec). In practice, the image compression functionality (i.e. autoencoding) is also desirable, requiring to deploy alongside I2Icodec a regular image codec. Thus, we further propose a unified framework that allows both translation and autoencoding capabilities in a single codec. Adaptive residual blocks conditioned on the translation/compression mode provide flexible adaptation to the desired functionality. The experiments show promising results in both I2I translation and image compression using a single model. | ||||
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| Notes | LAMP | Approved | no | ||
| Call Number | Admin @ si @ YWH2022 | Serial | 3679 | ||
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| Author | Patricia Suarez; Dario Carpio; Angel Sappa | ||||
| Title | Enhancement of guided thermal image super-resolution approaches | Type | Journal Article | ||
| Year | 2024 | Publication | Neurocomputing | Abbreviated Journal |
NEUCOM |
| Volume | 573 | Issue | 127197 | Pages | 1-17 |
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| Abstract | Guided image processing techniques are widely used to extract meaningful information from a guiding image and facilitate the enhancement of the guided one. This paper specifically addresses the challenge of guided thermal image super-resolution, where a low-resolution thermal image is enhanced using a high-resolution visible spectrum image. We propose a new strategy that enhances outcomes from current guided super-resolution methods. This is achieved by transforming the initial guiding data into a representation resembling a thermal-like image, which is more closely in sync with the intended output. Experimental results with upscale factors of 8 and 16, demonstrate the outstanding performance of our approach in guided thermal image super-resolution obtained by mapping the original guiding information to a thermal-like image representation. | ||||
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| Notes | MSIAU | Approved | no | ||
| Call Number | Admin @ si @ SCS2024 | Serial | 3998 | ||
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| Author | Francisco Javier Orozco; Xavier Roca; Jordi Gonzalez | ||||
| Title | Real-Time Gaze Tracking with Appearance-Based Models | Type | Journal Article | ||
| Year | 2008 | Publication | Machine Vision Applications | Abbreviated Journal |
MVAP |
| Volume | 20 | Issue | 6 | Pages | 353-364 |
| Keywords | Keywords Eyelid and iris tracking, Appearance models, Blinking, Iris saccade, Real-time gaze tracking | ||||
| Abstract | Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our
method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques.Thus, in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes. |
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ ORG2008 | Serial | 972 | ||
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| Author | Thierry Brouard; Jordi Gonzalez; Caifeng Shan; Massimo Piccardi; Larry S. Davis | ||||
| Title | Special issue on background modeling for foreground detection in real-world dynamic scenes | Type | Journal Article | ||
| Year | 2014 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 25 | Issue | 5 | Pages | 1101-1103 |
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| Abstract | Although background modeling and foreground detection are not mandatory steps for computer vision applications, they may prove useful as they separate the primal objects usually called “foreground” from the remaining part of the scene called “background”, and permits different algorithmic treatment in the video processing field such as video surveillance, optical motion capture, multimedia applications, teleconferencing and human–computer interfaces. Conventional background modeling methods exploit the temporal variation of each pixel to model the background, and the foreground detection is made using change detection. The last decade witnessed very significant publications on background modeling but recently new applications in which background is not static, such as recordings taken from mobile devices or Internet videos, need new developments to detect robustly moving objects in challenging environments. Thus, effective methods for robustness to deal both with dynamic backgrounds, i | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE; 600.078 | Approved | no | ||
| Call Number | BGS2014a | Serial | 2411 | ||
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| Author | Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg | ||||
| Title | Painting-91: A Large Scale Database for Computational Painting Categorization | Type | Journal Article | ||
| Year | 2014 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 25 | Issue | 6 | Pages | 1385-1397 |
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| Abstract | Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ KBW2014 | Serial | 2510 | ||
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| Author | Mariella Dimiccoli; Jean-Pascal Jacob; Lionel Moisan | ||||
| Title | Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach | Type | Journal Article | ||
| Year | 2016 | Publication | Journal of Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 27 | Issue | Pages | 511-527 | |
| Keywords | particle detection; particle tracking; a-contrario approach; time-lapse fluorescence imaging | ||||
| Abstract | In this work, we propose a probabilistic approach for the detection and the
tracking of particles on biological images. In presence of very noised and poor quality data, particles and trajectories can be characterized by an a-contrario model, that estimates the probability of observing the structures of interest in random data. This approach, first introduced in the modeling of human visual perception and then successfully applied in many image processing tasks, leads to algorithms that do not require a previous learning stage, nor a tedious parameter tuning and are very robust to noise. Comparative evaluations against a well established baseline show that the proposed approach outperforms the state of the art. |
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| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @ DJM2016 | Serial | 2735 | ||
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| Author | Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
| Title | Growing Algorithm for Intersection Detection (GRAID) in branching patterns | Type | Journal Article | ||
| Year | 2015 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 26 | Issue | 2 | Pages | 387-400 |
| Keywords | Bifurcation ; Crossroad; Intersection ;Retina ; Vessel | ||||
| Abstract | Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed. | ||||
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| Notes | ;SIAI | Approved | no | ||
| Call Number | Admin @ si @MBS2015 | Serial | 2777 | ||
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| Author | F. Javier Sanchez; Jorge Bernal; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach | ||||
| Title | Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos | Type | Journal Article | ||
| Year | 2017 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | Issue | Pages | 1-20 | ||
| Keywords | Specular highlights; bright spot regions segmentation; region classification; colonoscopy | ||||
| Abstract | A novel specular highlights detection method in colonoscopy videos is presented. The method is based on a model of appearance de ning specular
highlights as bright spots which are highly contrasted with respect to adjacent regions. Our approach proposes two stages; segmentation, and then classi cation of bright spot regions. The former de nes a set of candidate regions obtained through a region growing process with local maxima as initial region seeds. This process creates a tree structure which keeps track, at each growing iteration, of the region frontier contrast; nal regions provided depend on restrictions over contrast value. Non-specular regions are ltered through a classi cation stage performed by a linear SVM classi er using model-based features from each region. We introduce a new validation database with more than 25; 000 regions along with their corresponding pixel-wise annotations. We perform a comparative study against other approaches. Results show that our method is superior to other approaches, with our segmented regions being closer to actual specular regions in the image. Finally, we also present how our methodology can also be used to obtain an accurate prediction of polyp histology. |
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| Notes | MV; 600.096; 600.175 | Approved | no | ||
| Call Number | Admin @ si @ SBS2017 | Serial | 2975 | ||
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| Author | Lu Yu; Lichao Zhang; Joost Van de Weijer; Fahad Shahbaz Khan; Yongmei Cheng; C. Alejandro Parraga | ||||
| Title | Beyond Eleven Color Names for Image Understanding | Type | Journal Article | ||
| Year | 2018 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 29 | Issue | 2 | Pages | 361-373 |
| Keywords | Color name; Discriminative descriptors; Image classification; Re-identification; Tracking | ||||
| Abstract | Color description is one of the fundamental problems of image understanding. One of the popular ways to represent colors is by means of color names. Most existing work on color names focuses on only the eleven basic color terms of the English language. This could be limiting the discriminative power of these representations, and representations based on more color names are expected to perform better. However, there exists no clear strategy to choose additional color names. We collect a dataset of 28 additional color names. To ensure that the resulting color representation has high discriminative power we propose a method to order the additional color names according to their complementary nature with the basic color names. This allows us to compute color name representations with high discriminative power of arbitrary length. In the experiments we show that these new color name descriptors outperform the existing color name descriptor on the task of visual tracking, person re-identification and image classification. | ||||
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| Notes | LAMP; NEUROBIT; 600.068; 600.109; 600.120 | Approved | no | ||
| Call Number | Admin @ si @ YYW2018 | Serial | 3087 | ||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Muhammad Anwer Rao; Andrew Bagdanov; Michael Felsberg; Jorma | ||||
| Title | Scale coding bag of deep features for human attribute and action recognition | Type | Journal Article | ||
| Year | 2018 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 29 | Issue | 1 | Pages | 55-71 |
| Keywords | Action recognition; Attribute recognition; Bag of deep features | ||||
| Abstract | Most approaches to human attribute and action recognition in still images are based on image representation in which multi-scale local features are pooled across scale into a single, scale-invariant encoding. Both in bag-of-words and the recently popular representations based on convolutional neural networks, local features are computed at multiple scales. However, these multi-scale convolutional features are pooled into a single scale-invariant representation. We argue that entirely scale-invariant image representations are sub-optimal and investigate approaches to scale coding within a bag of deep features framework. Our approach encodes multi-scale information explicitly during the image encoding stage. We propose two strategies to encode multi-scale information explicitly in the final image representation. We validate our two scale coding techniques on five datasets: Willow, PASCAL VOC 2010, PASCAL VOC 2012, Stanford-40 and Human Attributes (HAT-27). On all datasets, the proposed scale coding approaches outperform both the scale-invariant method and the standard deep features of the same network. Further, combining our scale coding approaches with standard deep features leads to consistent improvement over the state of the art. | ||||
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| Notes | LAMP; 600.068; 600.079; 600.106; 600.120 | Approved | no | ||
| Call Number | Admin @ si @ KWR2018 | Serial | 3107 | ||
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| Author | Albert Clapes; Alex Pardo; Oriol Pujol; Sergio Escalera | ||||
| Title | Action detection fusing multiple Kinects and a WIMU: an application to in-home assistive technology for the elderly | Type | Journal Article | ||
| Year | 2018 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVAP |
| Volume | 29 | Issue | 5 | Pages | 765–788 |
| Keywords | Multimodal activity detection; Computer vision; Inertial sensors; Dense trajectories; Dynamic time warping; Assistive technology | ||||
| Abstract | We present a vision-inertial system which combines two RGB-Depth devices together with a wearable inertial movement unit in order to detect activities of the daily living. From multi-view videos, we extract dense trajectories enriched with a histogram of normals description computed from the depth cue and bag them into multi-view codebooks. During the later classification step a multi-class support vector machine with a RBF- 2 kernel combines the descriptions at kernel level. In order to perform action detection from the videos, a sliding window approach is utilized. On the other hand, we extract accelerations, rotation angles, and jerk features from the inertial data collected by the wearable placed on the user’s dominant wrist. During gesture spotting, a dynamic time warping is applied and the aligning costs to a set of pre-selected gesture sub-classes are thresholded to determine possible detections. The outputs of the two modules are combined in a late-fusion fashion. The system is validated in a real-case scenario with elderly from an elder home. Learning-based fusion results improve the ones from the single modalities, demonstrating the success of such multimodal approach. | ||||
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| Notes | HUPBA; no proj | Approved | no | ||
| Call Number | Admin @ si @ CPP2018 | Serial | 3125 | ||
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| Author | Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva | ||||
| Title | On Tracking Inside Groups | Type | Journal Article | ||
| Year | 2010 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVA |
| Volume | 21 | Issue | 2 | Pages | 113–127 |
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| Abstract | This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ RGP2010 | Serial | 1158 | ||
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| Author | Sergio Escalera; Oriol Pujol; Petia Radeva | ||||
| Title | Traffic sign recognition system with β -correction | Type | Journal Article | ||
| Year | 2010 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVA |
| Volume | 21 | Issue | 2 | Pages | 99–111 |
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| Abstract | Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2010a | Serial | 1276 | ||
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| Author | Bogdan Raducanu; Fadi Dornaika | ||||
| Title | Texture-independent recognition of facial expressions in image snapshots and videos | Type | Journal Article | ||
| Year | 2013 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVA |
| Volume | 24 | Issue | 4 | Pages | 811-820 |
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| Abstract | This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR; 600.046; 605.203;MV | Approved | no | ||
| Call Number | Admin @ si @ RaD2013 | Serial | 2230 | ||
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| Author | Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester | ||||
| Title | Geometric Steerable Medial Maps | Type | Journal Article | ||
| Year | 2013 | Publication | Machine Vision and Applications | Abbreviated Journal |
MVA |
| Volume | 24 | Issue | 6 | Pages | 1255-1266 |
| Keywords | Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction | ||||
| Abstract | In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. |
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Mubarak Shah | |
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| ISSN | 0932-8092 | ISBN | Medium | ||
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| Notes | IAM; 605.203; 600.060; 600.044 | Approved | no | ||
| Call Number | IAM @ iam @ VGB2013 | Serial | 2192 | ||
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