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| Author | Diego Cheda; Daniel Ponsa; Antonio Lopez | ||||
| Title | Monocular Egomotion Estimation based on Image Matching | Type | Conference Article | ||
| Year | 2012 | Publication | 1st International Conference on Pattern Recognition Applications and Methods | Abbreviated Journal | |
| Volume | Issue | Pages  |
425-430 | ||
| Keywords | SLAM | ||||
| Abstract | |||||
| Address | Portugal | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICPRAM | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ CPL2012a;; ADAS @ adas @ | Serial | 2011 | ||
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| Author | Marcel P. Lucassen; Theo Gevers; Arjan Gijsenij | ||||
| Title | Texture Affects Color Emotion | Type | Journal Article | ||
| Year | 2011 | Publication | Color Research & Applications | Abbreviated Journal | CRA |
| Volume | 36 | Issue | 6 | Pages |
426–436 |
| Keywords | color;texture;color emotion;observer variability;ranking | ||||
| Abstract | Several studies have recorded color emotions in subjects viewing uniform color (UC) samples. We conduct an experiment to measure and model how these color emotions change when texture is added to the color samples. Using a computer monitor, our subjects arrange samples along four scales: warm–cool, masculine–feminine, hard–soft, and heavy–light. Three sample types of increasing visual complexity are used: UC, grayscale textures, and color textures (CTs). To assess the intraobserver variability, the experiment is repeated after 1 week. Our results show that texture fully determines the responses on the Hard-Soft scale, and plays a role of decreasing weight for the masculine–feminine, heavy–light, and warm–cool scales. Using some 25,000 observer responses, we derive color emotion functions that predict the group-averaged scale responses from the samples' color and texture parameters. For UC samples, the accuracy of our functions is significantly higher (average R2 = 0.88) than that of previously reported functions applied to our data. The functions derived for CT samples have an accuracy of R2 = 0.80. We conclude that when textured samples are used in color emotion studies, the psychological responses may be strongly affected by texture. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010 | ||||
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| Area | Expedition | Conference | |||
| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ LGG2011 | Serial | 1844 | ||
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| Author | Fadi Dornaika; Angel Sappa | ||||
| Title | Evaluation of an Appearance-based 3D Face Tracker using Dense 3D Data | Type | Journal | ||
| Year | 2008 | Publication | Machine Vision and Applications | Abbreviated Journal | |
| Volume | 19 | Issue | 5-6 | Pages |
427–441 |
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ DoS2008b | Serial | 1018 | ||
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| Author | Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta | ||||
| Title | Structure-Preserving Smoothing of Biomedical Images | Type | Conference Article | ||
| Year | 2009 | Publication | 13th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 5702 | Issue | Pages |
427-434 | |
| Keywords | non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography. | ||||
| Abstract | Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. | ||||
| Address | Münster, Germany | ||||
| Corporate Author | Thesis | ||||
| 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 | 978-3-642-03766-5 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ GHB2009 | Serial | 1527 | ||
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| Author | Luis Herranz; Shuqiang Jiang; Ruihan Xu | ||||
| Title | Modeling Restaurant Context for Food Recognition | Type | Journal Article | ||
| Year | 2017 | Publication | IEEE Transactions on Multimedia | Abbreviated Journal | TMM |
| Volume | 19 | Issue | 2 | Pages |
430 - 440 |
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| Abstract | Food photos are widely used in food logs for diet monitoring and in social networks to share social and gastronomic experiences. A large number of these images are taken in restaurants. Dish recognition in general is very challenging, due to different cuisines, cooking styles, and the intrinsic difficulty of modeling food from its visual appearance. However, contextual knowledge can be crucial to improve recognition in such scenario. In particular, geocontext has been widely exploited for outdoor landmark recognition. Similarly, we exploit knowledge about menus and location of restaurants and test images. We first adapt a framework based on discarding unlikely categories located far from the test image. Then, we reformulate the problem using a probabilistic model connecting dishes, restaurants, and locations. We apply that model in three different tasks: dish recognition, restaurant recognition, and location refinement. Experiments on six datasets show that by integrating multiple evidences (visual, location, and external knowledge) our system can boost the performance in all tasks. | ||||
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| Notes | LAMP; 600.120 | Approved | no | ||
| Call Number | Admin @ si @ HJX2017 | Serial | 2965 | ||
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| Author | Oriol Pujol; Petia Radeva | ||||
| Title | Texture Segmentation by Statistical Deformable Models | Type | Journal | ||
| Year | 2004 | Publication | International Journal of Image and Graphics | Abbreviated Journal | IJIG |
| Volume | 4 | Issue | 3 | Pages |
433-452 |
| Keywords | Texture segmentation, parametric active contours, statistic snakes | ||||
| Abstract | Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model. | ||||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PuR2004a | Serial | 505 | ||
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| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga | ||||
| Title | Saliency Estimation Using a Non-Parametric Low-Level Vision Model | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
433-440 | ||
| Keywords | Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms | ||||
| Abstract | Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. | ||||
| Address | Colorado Springs | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | 978-1-4577-0394-2 | Medium | |
| Area | Expedition | Conference | CVPR | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MVO2011 | Serial | 1757 | ||
| Permanent link to this record | |||||
| 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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| Series Volume | Series Issue | Edition | |||
| ISSN | 1932-4553 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ BLS2012b | Serial | 2155 | ||
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| Author | Frederic Sampedro; Sergio Escalera | ||||
| Title | Spatial codification of label predictions in Multi-scale Stacked Sequential Learning: A case study on multi-class medical volume segmentation | Type | Journal Article | ||
| Year | 2015 | Publication | IET Computer Vision | Abbreviated Journal | IETCV |
| Volume | 9 | Issue | 3 | Pages |
439 - 446 |
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| Abstract | In this study, the authors propose the spatial codification of label predictions within the multi-scale stacked sequential learning (MSSL) framework, a successful learning scheme to deal with non-independent identically distributed data entries. After providing a motivation for this objective, they describe its theoretical framework based on the introduction of the blurred shape model as a smart descriptor to codify the spatial distribution of the predicted labels and define the new extended feature set for the second stacked classifier. They then particularise this scheme to be applied in volume segmentation applications. Finally, they test the implementation of the proposed framework in two medical volume segmentation datasets, obtaining significant performance improvements (with a 95% of confidence) in comparison to standard Adaboost classifier and classical MSSL approaches. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1751-9632 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SaE2015 | Serial | 2551 | ||
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| Author | Alicia Fornes; Beata Megyesi; Joan Mas | ||||
| Title | Transcription of Encoded Manuscripts with Image Processing Techniques | Type | Conference Article | ||
| Year | 2017 | Publication | Digital Humanities Conference | Abbreviated Journal | |
| Volume | Issue | Pages |
441-443 | ||
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| Area | Expedition | Conference | DH | ||
| Notes | DAG; 600.097; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ FMM2017 | Serial | 3061 | ||
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| Author | Josep Famadas; Meysam Madadi; Cristina Palmero; Sergio Escalera | ||||
| Title | Generative Video Face Reenactment by AUs and Gaze Regularization | Type | Conference Article | ||
| Year | 2020 | Publication | 15th IEEE International Conference on Automatic Face and Gesture Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
444-451 | ||
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| Abstract | In this work, we propose an encoder-decoder-like architecture to perform face reenactment in image sequences. Our goal is to transfer the training subject identity to a given test subject. We regularize face reenactment by facial action unit intensity and 3D gaze vector regression. This way, we enforce the network to transfer subtle facial expressions and eye dynamics, providing a more lifelike result. The proposed encoder-decoder receives as input the previous sequence frame stacked to the current frame image of facial landmarks. Thus, the generated frames benefit from appearance and geometry, while keeping temporal coherence for the generated sequence. At test stage, a new target subject with the facial performance of the source subject and the appearance of the training subject is reenacted. Principal component analysis is applied to project the test subject geometry to the closest training subject geometry before reenactment. Evaluation of our proposal shows faster convergence, and more accurate and realistic results in comparison to other architectures without action units and gaze regularization. | ||||
| Address | Virtual; November 2020 | ||||
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| Area | Expedition | Conference | FG | ||
| Notes | HUPBA | Approved | no | ||
| Call Number | Admin @ si @ FMP2020 | Serial | 3517 | ||
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| Author | Sergio Escalera; Jordi Gonzalez; Xavier Baro; Miguel Reyes; Oscar Lopes; Isabelle Guyon; V. Athitsos; Hugo Jair Escalante | ||||
| Title | Multi-modal Gesture Recognition Challenge 2013: Dataset and Results | Type | Conference Article | ||
| Year | 2013 | Publication | 15th ACM International Conference on Multimodal Interaction | Abbreviated Journal | |
| Volume | Issue | Pages |
445-452 | ||
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| Abstract | The recognition of continuous natural gestures is a complex and challenging problem due to the multi-modal nature of involved visual cues (e.g. fingers and lips movements, subtle facial expressions, body pose, etc.), as well as technical limitations such as spatial and temporal resolution and unreliable
depth cues. In order to promote the research advance on this field, we organized a challenge on multi-modal gesture recognition. We made available a large video database of 13; 858 gestures from a lexicon of 20 Italian gesture categories recorded with a KinectTM camera, providing the audio, skeletal model, user mask, RGB and depth images. The focus of the challenge was on user independent multiple gesture learning. There are no resting positions and the gestures are performed in continuous sequences lasting 1-2 minutes, containing between 8 and 20 gesture instances in each sequence. As a result, the dataset contains around 1:720:800 frames. In addition to the 20 main gesture categories, ‘distracter’ gestures are included, meaning that additional audio and gestures out of the vocabulary are included. The final evaluation of the challenge was defined in terms of the Levenshtein edit distance, where the goal was to indicate the real order of gestures within the sequence. 54 international teams participated in the challenge, and outstanding results were obtained by the first ranked participants. |
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| Address | Sidney; Australia; December 2013 | ||||
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| ISSN | ISBN | 978-1-4503-2129-7 | Medium | ||
| Area | Expedition | Conference | ICMI | ||
| Notes | HUPBA; ISE; 600.063;MV | Approved | no | ||
| Call Number | Admin @ si @ EGB2013 | Serial | 2373 | ||
| Permanent link to this record | |||||
| Author | Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate | ||||
| Title | Local Analysis of Confidence Measures for Optical Flow Quality Evaluation | Type | Conference Article | ||
| Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 3 | Issue | Pages |
450-457 | |
| Keywords | Optical Flow; Confidence Measure; Performance Evaluation. | ||||
| Abstract | Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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| Address | Lisboa; January 2014 | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ MGM2014 | Serial | 2432 | ||
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| Author | Joan Mas; Gemma Sanchez; Josep Llados; B. Lamiroy | ||||
| Title | An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams | Type | Conference Article | ||
| Year | 2007 | Publication | 9th IEEE International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | 1 | Issue | Pages |
452–456 | |
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| Address | Curitiba (Brazil) | ||||
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| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ MSL2007a | Serial | 847 | ||
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| Author | Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas | ||||
| Title | Evaluating Real-Time Mirroring of Head Gestures using Smart Glasses | Type | Conference Article | ||
| Year | 2015 | Publication | 16th IEEE International Conference on Computer Vision Workshops | Abbreviated Journal | |
| Volume | Issue | Pages |
452-460 | ||
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| Abstract | Mirroring occurs when one person tends to mimic the non-verbal communication of their counterparts. Even though mirroring is a complex phenomenon, in this study, we focus on the detection of head-nodding as a simple non-verbal communication cue due to its significance as a gesture displayed during social interactions. This paper introduces a computer vision-based method to detect mirroring through the analysis of head gestures using wearable cameras (smart glasses). In addition, we study how such a method can be used to explore perceived competence. The proposed method has been evaluated and the experiments demonstrate how static and wearable cameras seem to be equally effective to gather the information required for the analysis. | ||||
| Address | Santiago de Chile; December 2015 | ||||
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| Area | Expedition | Conference | ICCVW | ||
| Notes | LAMP; 600.068; 600.072; | Approved | no | ||
| Call Number | Admin @ si @ TRM2015 | Serial | 2722 | ||
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