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Debora Gil; Oriol Ramos Terrades; Raquel Perez |
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Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution |
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Conference Article |
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2020 |
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Women in Geometry and Topology |
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Barcelona; September 2019 |
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IAM; DAG; 600.139; 600.145; 600.121 |
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Admin @ si @ GRP2020 |
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3473 |
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Debora Gil; Oriol Ramos Terrades; Raquel Perez |
![goto web page (via DOI) doi](img/doi.gif)
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution |
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2021 |
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Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 |
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15 |
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89–93 |
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Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces. |
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Springer Nature |
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IAM; DAG; 600.120; 600.145; 600.139 |
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Admin @ si @ GRP2021 |
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3594 |
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Mustafa Hajij; Mathilde Papillon; Florian Frantzen; Jens Agerberg; Ibrahem AlJabea; Ruben Ballester; Claudio Battiloro; Guillermo Bernardez; Tolga Birdal; Aiden Brent; Peter Chin; Sergio Escalera; Simone Fiorellino; Odin Hoff Gardaa; Gurusankar Gopalakrishnan; Devendra Govil; Josef Hoppe; Maneel Reddy Karri; Jude Khouja; Manuel Lecha; Neal Livesay; Jan Meibner; Soham Mukherjee; Alexander Nikitin; Theodore Papamarkou; Jaro Prilepok; Karthikeyan Natesan Ramamurthy; Paul Rosen; Aldo Guzman-Saenz; Alessandro Salatiello; Shreyas N. Samaga; Simone Scardapane; Michael T. Schaub; Luca Scofano; Indro Spinelli; Lev Telyatnikov; Quang Truong; Robin Walters; Maosheng Yang; Olga Zaghen; Ghada Zamzmi; Ali Zia; Nina Miolane |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains |
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Miscellaneous |
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2024 |
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Arxiv |
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We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. TopoX consists of three packages: TopoNetX facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; TopoEmbedX provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; TopoModelx is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains. The extensively documented and unit-tested source code of TopoX is available under MIT license at this https URL. |
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HUPBA |
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Admin @ si @ HPF2024 |
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4021 |
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Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Touching Text Character Localization in Graphical Documents using SIFT |
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Conference Article |
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2009 |
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In proceedings 8th IAPR International Workshop on Graphics Recognition |
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Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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La rochelle; July 2009 |
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GREC |
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DAG |
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DAG @ dag @ RPL2009c |
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1445 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Touching Text Character Localization in Graphical Documents using SIFT |
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Book Chapter |
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2010 |
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Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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199-211 |
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Support Vector Machine; Text Component; Graphical Line; Document Image; Scale Invariant Feature Transform |
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Abstract |
Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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DAG |
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Admin @ si @ RPL2010c |
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2408 |
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Author |
Patricia Suarez; Angel Sappa |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Toward a Thermal Image-Like Representation |
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Conference Article |
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2023 |
Publication |
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
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133-140 |
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This paper proposes a novel model to obtain thermal image-like representations to be used as an input in any thermal image compressive sensing approach (e.g., thermal image: filtering, enhancing, super-resolution). Thermal images offer interesting information about the objects in the scene, in addition to their temperature. Unfortunately, in most of the cases thermal cameras acquire low resolution/quality images. Hence, in order to improve these images, there are several state-of-the-art approaches that exploit complementary information from a low-cost channel (visible image) to increase the image quality of an expensive channel (infrared image). In these SOTA approaches visible images are fused at different levels without paying attention the images acquire information at different bands of the spectral. In this paper a novel approach is proposed to generate thermal image-like representations from a low cost visible images, by means of a contrastive cycled GAN network. Obtained representations (synthetic thermal image) can be later on used to improve the low quality thermal image of the same scene. Experimental results on different datasets are presented. |
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Lisboa; Portugal; February 2023 |
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VISIGRAPP |
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MSIAU |
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Admin @ si @ SuS2023b |
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3927 |
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Author |
X. Varona; Antoni Jaume-i-Capo; Jordi Gonzalez; Francisco Jose Perales |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Toward Natural Interaction through Visual Recognition of Body Gestures in Real-Time |
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2008 |
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Interacting with Computers, diu 10,1016/j.intcom.2008.10.001, available on line |
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ISE @ ise @ VJG2008 |
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1022 |
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Author |
Marco Pedersoli; Jordi Gonzalez; Xu Hu; Xavier Roca |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Toward Real-Time Pedestrian Detection Based on a Deformable Template Model |
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Journal Article |
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Year |
2014 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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15 |
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1 |
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355-364 |
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Most advanced driving assistance systems already include pedestrian detection systems. Unfortunately, there is still a tradeoff between precision and real time. For a reliable detection, excellent precision-recall such a tradeoff is needed to detect as many pedestrians as possible while, at the same time, avoiding too many false alarms; in addition, a very fast computation is needed for fast reactions to dangerous situations. Recently, novel approaches based on deformable templates have been proposed since these show a reasonable detection performance although they are computationally too expensive for real-time performance. In this paper, we present a system for pedestrian detection based on a hierarchical multiresolution part-based model. The proposed system is able to achieve state-of-the-art detection accuracy due to the local deformations of the parts while exhibiting a speedup of more than one order of magnitude due to a fast coarse-to-fine inference technique. Moreover, our system explicitly infers the level of resolution available so that the detection of small examples is feasible with a very reduced computational cost. We conclude this contribution by presenting how a graphics processing unit-optimized implementation of our proposed system is suitable for real-time pedestrian detection in terms of both accuracy and speed. |
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1524-9050 |
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ISE; 601.213; 600.078 |
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PGH2014 |
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2350 |
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Author |
Carlo Gatta; Juan Diego Gomez; Francesco Ciompi; O. Rodriguez-Leor; Petia Radeva |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Toward robust myocardial blush grade estimation in contrast angiography |
Type |
Conference Article |
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2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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249–256 |
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The assessment of Myocardial Blush Grade after primary angioplasty is a precious diagnostic tool to understand if the patient needs further medication or the use of specifics drugs. Unfortunately, the assessment of MBG is difficult for non highly specialized staff. Experimental data show that there is poor correlation between MBG assessment of low and high specialized staff, thus reducing its applicability. This paper proposes a method able to achieve an objective measure of MBG, or a set of parameters that correlates with the MBG. The method tracks the blush area starting from just one single frame tagged by the physician. As a consequence, the blush area is kept isolated from contaminating phenomena such as diaphragm and arteries movements. We also present a method to extract four parameters that are expected to correlate with the MBG. Preliminary results show that the method is capable of extracting interesting information regarding the behavior of the myocardial perfusion. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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MILAB |
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BCNPCL @ bcnpcl @ GGC2009 |
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1161 |
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Author |
Juan Diego Gomez |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Toward Robust Myocardial Blush Grade Estimation in Contrast Angiography |
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Report |
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2009 |
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CVC Technical Report |
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134 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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Admin @ si @ Gom2009 |
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2393 |
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Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Toward the Detection of Urban Infrastructures Edge Shadows |
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Conference Article |
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2010 |
Publication |
12th International Conference on Advanced Concepts for Intelligent Vision Systems |
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6474 |
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I |
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30–37 |
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In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising. |
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Sydney, Australia |
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Springer Berlin Heidelberg |
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eds. Blanc–Talon et al |
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0302-9743 |
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978-3-642-17687-6 |
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ACIVS |
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OR;MV |
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BCNPCL @ bcnpcl @ ISR2010 |
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1458 |
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Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks |
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2018 |
Publication |
Journal of Medical Robotics Research |
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JMRR |
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3 |
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2 |
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convolutional neural networks; colonoscopy; computer aided diagnosis |
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Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp
detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance. |
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MV; no menciona |
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BZM2018 |
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2976 |
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Author |
C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
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Towards a general model of colour categorization which considers context |
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Journal Article |
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2010 |
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Perception. ECVP Abstract Supplement |
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PER |
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39 |
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86 |
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In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly dierent(more diuse) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we
completed our parametric fuzzy-sets model of colour naming space. |
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CIC |
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CAT @ cat @ PBV2010b |
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1326 |
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Author |
Arnau Baro; Jialuo Chen; Alicia Fornes; Beata Megyesi |
![download PDF file pdf](img/file_PDF.gif)
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Towards a generic unsupervised method for transcription of encoded manuscripts |
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Conference Article |
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2019 |
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3rd International Conference on Digital Access to Textual Cultural Heritage |
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73-78 |
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A. Baró, J. Chen, A. Fornés, B. Megyesi. |
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Historical ciphers, a special type of manuscripts, contain encrypted information, important for the interpretation of our history. The first step towards decipherment is to transcribe the images, either manually or by automatic image processing techniques. Despite the improvements in handwritten text recognition (HTR) thanks to deep learning methodologies, the need of labelled data to train is an important limitation. Given that ciphers often use symbol sets across various alphabets and unique symbols without any transcription scheme available, these supervised HTR techniques are not suitable to transcribe ciphers. In this paper we propose an un-supervised method for transcribing encrypted manuscripts based on clustering and label propagation, which has been successfully applied to community detection in networks. We analyze the performance on ciphers with various symbol sets, and discuss the advantages and drawbacks compared to supervised HTR methods. |
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Brussels; May 2019 |
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DATeCH |
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DAG; 600.097; 600.140; 600.121 |
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Admin @ si @ BCF2019 |
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3276 |
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Author |
Justine Giroux; Mohammad Reza Karimi Dastjerdi; Yannick Hold-Geoffroy; Javier Vazquez; Jean François Lalonde |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Towards a Perceptual Evaluation Framework for Lighting Estimation |
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2024 |
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Arxiv |
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rogress in lighting estimation is tracked by computing existing image quality assessment (IQA) metrics on images from standard datasets. While this may appear to be a reasonable approach, we demonstrate that doing so does not correlate to human preference when the estimated lighting is used to relight a virtual scene into a real photograph. To study this, we design a controlled psychophysical experiment where human observers must choose their preference amongst rendered scenes lit using a set of lighting estimation algorithms selected from the recent literature, and use it to analyse how these algorithms perform according to human perception. Then, we demonstrate that none of the most popular IQA metrics from the literature, taken individually, correctly represent human perception. Finally, we show that by learning a combination of existing IQA metrics, we can more accurately represent human preference. This provides a new perceptual framework to help evaluate future lighting estimation algorithms. |
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Seattle; USA; June 2024 |
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CVPR |
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MACO; CIC |
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Admin @ si @ GDH2024 |
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3999 |
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