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Author |
Albert Andaluz |
![download PDF file pdf](img/file_PDF.gif)
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
LV Contour Segmentation in TMR images using Semantic Description of Tissue and Prior Knowledge Correction |
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Report |
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2009 |
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CVC Technical Report |
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142 |
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Active Contour Models; Snakes; Active Shape Models; Deformable Templates; Left Ventricle Segmentation; Generalized Orthogonal Procrustes Analysis; Harmonic Phase Flow; Principal Component Analysis; Tagged Magnetic Resonance |
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The Diagnosis of Left Ventricle (LV) pathologies is related to regional wall motion analysis. Health indicator scores such as the rotation and the torsion are useful for the diagnose of the Left Ventricle (LV) function. However, this requires proper identification of LV segments. On one hand, manual segmentation is robust, but it is slow and requires medical expertise. On the other hand, the tag pattern in Tagged Magnetic Resonance (TMR) sequences is a problem for the automatic segmentation of the LV boundaries. Consequently, we propose a method based in the classical formulation of parametric Snakes, combined with Active Shape models. Our semantic definition of the LV is tagged tissue that experiences motion in the systolic cycle. This defines two energy potentials for the Snake convergence. Additionally, the mean shape corrects excessive deviation from the anatomical shape. We have validated our approach in 15 healthy volunteers and two short axis cuts. In this way, we have compared the automatic segmentations to manual shapes outlined by medical experts. Also, we have explored the accuracy of clinical scores computed using automatic contours. The results show minor divergence in the approximation and the manual segmentations as well as robust computation of clinical scores in all cases. From this we conclude that the proposed method is a promising support tool for clinical analysis. |
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Master's thesis |
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Bellaterra 08193, Barcelona, Spain |
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IAM; |
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IAM @ iam @ And2009 |
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1667 |
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Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne |
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Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans |
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2011 |
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In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis |
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Toronto, Canada |
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PIA |
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MILAB;HuPBA |
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Admin @ si @ CPL2011 |
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1798 |
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Oriol Pujol; Petia Radeva |
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Lumen Detection in Ivus Image Using Snakes in a Statical Framework. |
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Miscellaneous |
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2002 |
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XX Congreso Anual de la Sociedad Española de Ingenieria Biomedica CASEIB 2002, 1: 129–132. |
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Saragossa, Espanya |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PuR2002 |
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315 |
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Swathikiran Sudhakaran; Sergio Escalera; Oswald Lanz |
![download PDF file pdf](img/file_PDF.gif)
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LSTA: Long Short-Term Attention for Egocentric Action Recognition |
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2019 |
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32nd IEEE Conference on Computer Vision and Pattern Recognition |
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9946-9955 |
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Egocentric activity recognition is one of the most challenging tasks in video analysis. It requires a fine-grained discrimination of small objects and their manipulation. While some methods base on strong supervision and attention mechanisms, they are either annotation consuming or do not take spatio-temporal patterns into account. In this paper we propose LSTA as a mechanism to focus on features from spatial relevant parts while attention is being tracked smoothly across the video sequence. We demonstrate the effectiveness of LSTA on egocentric activity recognition with an end-to-end trainable two-stream architecture, achieving state-of-the-art performance on four standard benchmarks. |
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California; June 2019 |
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CVPR |
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HuPBA; no proj |
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no |
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Admin @ si @ SEL2019 |
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3333 |
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Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
LSDE: Levenshtein Space Deep Embedding for Query-by-string Word Spotting |
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2017 |
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14th International Conference on Document Analysis and Recognition |
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n this paper we present the LSDE string representation and its application to handwritten word spotting. LSDE is a novel embedding approach for representing strings that learns a space in which distances between projected points are correlated with the Levenshtein edit distance between the original strings.
We show how such a representation produces a more semantically interpretable retrieval from the user’s perspective than other state of the art ones such as PHOC and DCToW. We also conduct a preliminary handwritten word spotting experiment on the George Washington dataset. |
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Kyoto; Japan; November 2017 |
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ICDAR |
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DAG; 600.084; 600.121 |
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Admin @ si @ GRK2017 |
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2999 |
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Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu |
![download PDF file pdf](img/file_PDF.gif)
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
LSDA Solution Schemes for Modelless 3D Head Pose Estimation |
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2012 |
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IEEE Workshop on the Applications of Computer Vision |
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393-398 |
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Breckenridge; USA; |
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WACV |
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OR;MV |
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Admin @ si @ DBR2012 |
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1889 |
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Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Low-level SpatioChromatic Grouping for Saliency Estimation |
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2013 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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35 |
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11 |
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2810-2816 |
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We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. |
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0162-8828 |
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CIC; 600.051; 600.052; 605.203 |
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Admin @ si @ MVO2013 |
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2289 |
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Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Low-dimensional and Comprehensive Color Texture Description |
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Journal Article |
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2012 |
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Computer Vision and Image Understanding |
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CVIU |
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116 |
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I |
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54-67 |
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Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are defined independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges).
A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent definition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz’s Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is defined from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap |
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1077-3142 |
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CAT;CIC |
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Admin @ si @ ASV2012 |
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1827 |
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Author |
Onur Ferhat; Fernando Vilariño |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Low Cost Eye Tracking: The Current Panorama |
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2016 |
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Computational Intelligence and Neuroscience |
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CIN |
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Article ID 8680541 |
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Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools. |
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MV; 605.103; 600.047; 600.097;SIAI |
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Admin @ si @ FeV2016 |
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2744 |
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Giacomo Magnifico; Beata Megyesi; Mohamed Ali Souibgui; Jialuo Chen; Alicia Fornes |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Lost in Transcription of Graphic Signs in Ciphers |
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2022 |
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International Conference on Historical Cryptology (HistoCrypt 2022) |
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153-158 |
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transcription of ciphers; hand-written text recognition of symbols; graphic signs |
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Hand-written Text Recognition techniques with the aim to automatically identify and transcribe hand-written text have been applied to historical sources including ciphers. In this paper, we compare the performance of two machine learning architectures, an unsupervised method based on clustering and a deep learning method with few-shot learning. Both models are tested on seen and unseen data from historical ciphers with different symbol sets consisting of various types of graphic signs. We compare the models and highlight their differences in performance, with their advantages and shortcomings. |
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Amsterdam, Netherlands, June 20-22, 2022 |
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HystoCrypt |
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DAG; 600.121; 600.162; 602.230; 600.140 |
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Admin @ si @ MBS2022 |
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3731 |
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Sergio Escalera; Oriol Pujol; Petia Radeva |
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Loss-Weighted Decoding for Error-Correcting Output Coding |
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2008 |
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3rd International Conference on Computer Vision Theory and Applications, |
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2 |
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117–122 |
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Madeira (Portugal) |
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VISAPP |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ EPR2008a |
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964 |
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Joan Serrat; Ferran Diego; Felipe Lumbreras |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Los faros delanteros a traves del objetivo |
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2008 |
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UAB Divulga, Revista de divulgacion cientifica |
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ADAS |
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ADAS @ adas @ SDL2008b |
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1471 |
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Valeriya Khan; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski |
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Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning |
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2023 |
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Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops |
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3496-3500 |
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In this work, we improve the generative replay in a continual learning setting. We notice that in VAE-based generative replay, the generated features are quite far from the original ones when mapped to the latent space. Therefore, we propose modifications that allow the model to learn and generate complex data. More specifically, we incorporate the distillation in latent space between the current and previous models to reduce feature drift. Additionally, a latent matching for the reconstruction and original data is proposed to improve generated features alignment. Further, based on the observation that the reconstructions are better for preserving knowledge, we add the cycling of generations through the previously trained model to make them closer to the original data. Our method outperforms other generative replay methods in various scenarios. |
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ICCVW |
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LAMP |
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Admin @ si @ KCT2023 |
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3942 |
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Sergio Escalera; Jordi Gonzalez; Hugo Jair Escalante; Xavier Baro; Isabelle Guyon |
![goto web page url](img/www.gif)
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Looking at People Special Issue |
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2018 |
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International Journal of Computer Vision |
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IJCV |
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126 |
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2-4 |
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141-143 |
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HUPBA; ISE; 600.119 |
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Admin @ si @ EGJ2018 |
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3093 |
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Author |
Murad Al Haj |
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Looking at Faces: Detection, Tracking and Pose Estimation |
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2013 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Humans can effortlessly perceive faces, follow them over space and time, and decode their rich content, such as pose, identity and expression. However, despite many decades of research on automatic facial perception in areas like face detection, expression recognition, pose estimation and face recognition, and despite many successes, a complete solution remains elusive. This thesis is dedicated to three problems in automatic face perception, namely face detection, face tracking and pose estimation.
In face detection, an initial simple model is presented that uses pixel-based heuristics to segment skin locations and hand-crafted rules to determine the locations of the faces present in an image. Different colorspaces are studied to judge whether a colorspace transformation can aid skin color detection. The output of this study is used in the design of a more complex face detector that is able to successfully generalize to different scenarios.
In face tracking, a framework that combines estimation and control in a joint scheme is presented to track a face with a single pan-tilt-zoom camera. While this work is mainly motivated by tracking faces, it can be easily applied atop of any detector to track different objects. The applicability of this method is demonstrated on simulated as well as real-life scenarios.
The last and most important part of this thesis is dedicate to monocular head pose estimation. In this part, a method based on partial least squares (PLS) regression is proposed to estimate pose and solve the alignment problem simultaneously. The contributions of this work are two-fold: 1) demonstrating that the proposed method achieves better than state-of-the-art results on the estimation problem and 2) developing a technique to reduce misalignment based on the learned PLS factors that outperform multiple instance learning (MIL) without the need for any re-training or the inclusion of misaligned samples in the training process, as normally done in MIL. |
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Barcelona |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Jordi Gonzalez;Xavier Roca |
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Admin @ si @ Haj2013 |
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2278 |
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