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| Author | Esteve Cervantes; Long Long Yu; Andrew Bagdanov; Marc Masana; Joost Van de Weijer | ||||
Title  |
Hierarchical Part Detection with Deep Neural Networks | Type | Conference Article | ||
| Year | 2016 | Publication | 23rd IEEE International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Object Recognition; Part Detection; Convolutional Neural Networks | ||||
| Abstract | Part detection is an important aspect of object recognition. Most approaches apply object proposals to generate hundreds of possible part bounding box candidates which are then evaluated by part classifiers. Recently several methods have investigated directly regressing to a limited set of bounding boxes from deep neural network representation. However, for object parts such methods may be unfeasible due to their relatively small size with respect to the image. We propose a hierarchical method for object and part detection. In a single network we first detect the object and then regress to part location proposals based only on the feature representation inside the object. Experiments show that our hierarchical approach outperforms a network which directly regresses the part locations. We also show that our approach obtains part detection accuracy comparable or better than state-of-the-art on the CUB-200 bird and Fashionista clothing item datasets with only a fraction of the number of part proposals. | ||||
| Address | Phoenix; Arizona; USA; September 2016 | ||||
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| Area | Expedition | Conference | ICIP | ||
| Notes | LAMP; 600.106 | Approved | no | ||
| Call Number | Admin @ si @ CLB2016 | Serial | 2762 | ||
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| Author | Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados | ||||
| Title |
Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents | Type | Book Chapter | ||
| Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
| Volume | 8746 | Issue | Pages | 25-37 | |
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| Abstract | Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Bart Lamiroy; Jean-Marc Ogier | |
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
| Area | Expedition | Conference | |||
| Notes | DAG; 600.045; 600.056; 600.061; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ BDJ2014 | Serial | 2699 | ||
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| Author | Anjan Dutta; Pau Riba; Josep Llados; Alicia Fornes | ||||
| Title |
Hierarchical Stochastic Graphlet Embedding for Graph-based Pattern Recognition | Type | Journal Article | ||
| Year | 2020 | Publication | Neural Computing and Applications | Abbreviated Journal | NEUCOMA |
| Volume | 32 | Issue | Pages | 11579–11596 | |
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| Abstract | Despite being very successful within the pattern recognition and machine learning community, graph-based methods are often unusable because of the lack of mathematical operations defined in graph domain. Graph embedding, which maps graphs to a vectorial space, has been proposed as a way to tackle these difficulties enabling the use of standard machine learning techniques. However, it is well known that graph embedding functions usually suffer from the loss of structural information. In this paper, we consider the hierarchical structure of a graph as a way to mitigate this loss of information. The hierarchical structure is constructed by topologically clustering the graph nodes and considering each cluster as a node in the upper hierarchical level. Once this hierarchical structure is constructed, we consider several configurations to define the mapping into a vector space given a classical graph embedding, in particular, we propose to make use of the stochastic graphlet embedding (SGE). Broadly speaking, SGE produces a distribution of uniformly sampled low-to-high-order graphlets as a way to embed graphs into the vector space. In what follows, the coarse-to-fine structure of a graph hierarchy and the statistics fetched by the SGE complements each other and includes important structural information with varied contexts. Altogether, these two techniques substantially cope with the usual information loss involved in graph embedding techniques, obtaining a more robust graph representation. This fact has been corroborated through a detailed experimental evaluation on various benchmark graph datasets, where we outperform the state-of-the-art methods. | ||||
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| Area | Expedition | Conference | |||
| Notes | DAG; 600.140; 600.121; 600.141 | Approved | no | ||
| Call Number | Admin @ si @ DRL2020 | Serial | 3348 | ||
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| Author | Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell | ||||
| Title |
High-Level Clothes Description Based on Color-Texture and Structural Features | Type | Book Chapter | ||
| Year | 2003 | Publication | Lecture Notes in Computer Science | Abbreviated Journal | |
| Volume | 2652 | Issue | Pages | 108–116 | |
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| Abstract | This work is a part of a surveillance system where content- based image retrieval is done in terms of people appearance. Given an image of a person, our work provides an automatic description of his clothing according to the colour, texture and structural composition of its garments. We present a two-stage process composed by image segmentation and a region-based interpretation. We segment an image by modelling it due to an attributed graph and applying a hybrid method that follows a split-and-merge strategy. We propose the interpretation of five cloth combinations that are modelled in a graph structure in terms of region features. The interpretation is viewed as a graph matching with an associated cost between the segmentation and the cloth models. Fi- nally, we have tested the process with a ground-truth of one hundred images. | ||||
| Address | Springer-Verlag | ||||
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| Notes | DAG;CIC | Approved | no | ||
| Call Number | CAT @ cat @ BTL2003a | Serial | 368 | ||
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| Author | Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell | ||||
| Title |
High-Level Clothes Description Based on Colour-Texture and Structural Features | Type | Conference Article | ||
| Year | 2003 | Publication | 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 | Abbreviated Journal | |
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| Address | Palma de Mallorca | ||||
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| Notes | DAG;CIC | Approved | no | ||
| Call Number | CAT @ cat @ BTL2003b | Serial | 369 | ||
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| Author | Agnes Borras | ||||
| Title |
High-Level Clothes Description Based on Colour-Texture Features. | Type | Miscellaneous | ||
| Year | 2002 | Publication | Director: J. Llados, Master Thesis. | Abbreviated Journal | |
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| Notes | Approved | no | |||
| Call Number | DAG @ dag @ Bor2002 | Serial | 322 | ||
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| Author | Marco Pedersoli; Jordi Gonzalez; Juan J. Villanueva | ||||
| Title |
High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients | Type | Conference Article | ||
| Year | 2009 | Publication | 4th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 5524 | Issue | Pages | ||
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| Abstract | This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated. Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration. |
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| Address | Póvoa de Varzim, Portugal | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-02171-8 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ PGV2009 | Serial | 1214 | ||
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| Author | David Guillamet; B. Moghaddam; Jordi Vitria | ||||
| Title |
Higher-Order Dependencies in Local Appearance Models | Type | Miscellaneous | ||
| Year | 2003 | Publication | IEEE International Conference on Image Processing (ICIP) | Abbreviated Journal | |
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| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ GMV2003b | Serial | 377 | ||
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| Author | Salvatore Tabbone; Oriol Ramos Terrades; S. Barrat | ||||
| Title |
Histogram of radon transform. A useful descriptor for shape retrieval | Type | Conference Article | ||
| Year | 2008 | Publication | 19th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1-4 | ||
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| Address | Tampa, Florida | ||||
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| Area | Expedition | Conference | ICPR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ TRB2008 | Serial | 1876 | ||
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| Author | Cristina Sanchez Montes; F. Javier Sanchez; Cristina Rodriguez de Miguel; Henry Cordova; Jorge Bernal; Maria Lopez Ceron; Josep Llach; Gloria Fernandez Esparrach | ||||
| Title |
Histological Prediction Of Colonic Polyps By Computer Vision. Preliminary Results | Type | Conference Article | ||
| Year | 2017 | Publication | 25th United European Gastroenterology Week | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | polyps; histology; computer vision | ||||
| Abstract | during colonoscopy, clinicians perform visual inspection of the polyps to predict histology. Kudo’s pit pattern classification is one of the most commonly used for optical diagnosis. These surface patterns present a contrast with respect to their neighboring regions and they can be considered as bright regions in the image that can attract the attention of computational methods. | ||||
| Address | Barcelona; October 2017 | ||||
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| Area | Expedition | Conference | ESGE | ||
| Notes | MV; no menciona | Approved | no | ||
| Call Number | Admin @ si @ SSR2017 | Serial | 2979 | ||
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| Author | Beata Megyesi; Alicia Fornes; Nils Kopal; Benedek Lang | ||||
| Title |
Historical Cryptology | Type | Book Chapter | ||
| Year | 2024 | Publication | Learning and Experiencing Cryptography with CrypTool and SageMath | Abbreviated Journal | |
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| Abstract | Historical cryptology studies (original) encrypted manuscripts, often handwritten sources, produced in our history. These historical sources can be found in archives, often hidden without any indexing and therefore hard to locate. Once found they need to be digitized and turned into a machine-readable text format before they can be deciphered with computational methods. The focus of historical cryptology is not primarily the development of sophisticated algorithms for decipherment, but rather the entire process of analysis of the encrypted source from collection and digitization to transcription and decryption. The process also includes the interpretation and contextualization of the message set in its historical context. There are many challenges on the way, such as mistakes made by the scribe, errors made by the transcriber, damaged pages, handwriting styles that are difficult to interpret, historical languages from various time periods, and hidden underlying language of the message. Ciphertexts vary greatly in terms of their code system and symbol sets used with more or less distinguishable symbols. Ciphertexts can be embedded in clearly written text, or shorter or longer sequences of cleartext can be embedded in the ciphertext. The ciphers used mostly in historical times are substitutions (simple, homophonic, or polyphonic), with or without nomenclatures, encoded as digits or symbol sequences, with or without spaces. So the circumstances are different from those in modern cryptography which focuses on methods (algorithms) and their strengths and assumes that the algorithm is applied correctly. For both historical and modern cryptology, attack vectors outside the algorithm are applied like implementation flaws and side-channel attacks. In this chapter, we give an introduction to the field of historical cryptology and present an overview of how researchers today process historical encrypted sources. | ||||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ MFK2024 | Serial | 4020 | ||
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| Author | Lluis Gomez; Dena Bazazian; Dimosthenis Karatzas | ||||
| Title |
Historical review of scene text detection research | Type | Book Chapter | ||
| Year | 2020 | Publication | Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis | Abbreviated Journal | |
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| Publisher | Springer | Place of Publication | Editor | K. Alahari; C.V. Jawahar | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Series on Advances in Computer Vision and Pattern Recognition | Abbreviated Series Title | ||
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| Notes | DAG; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ GBK2020 | Serial | 3495 | ||
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| Author | Joan Mas; Jose Antonio Rodriguez; Dimosthenis Karatzas; Gemma Sanchez; Josep Llados | ||||
| Title |
HistoSketch: A Semi-Automatic Annotation Tool for Archival Documents | Type | Conference Article | ||
| Year | 2008 | Publication | Proceedings of the 8th International Workshop on Document Analysis Systems, | Abbreviated Journal | |
| Volume | Issue | Pages | 517–524 | ||
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| Address | Nara (Japan) | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ MRK2008a | Serial | 1061 | ||
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| Author | Francesco Ciompi; Oriol Pujol; Carlo Gatta; Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title |
HoliMab: A Holistic Approach for Media-Adventitia Border Detection in Intravascular Ultrasound | Type | Journal Article | ||
| Year | 2012 | Publication | Medical Image Analysis | Abbreviated Journal | MIA |
| Volume | 16 | Issue | 6 | Pages | 1085-1100 |
| Keywords | Media–Adventitia border detection; Intravascular ultrasound; Multi-Scale Stacked Sequential Learning; Error-correcting output codes; Holistic segmentation | ||||
| Abstract | We present a fully automatic methodology for the detection of the Media-Adventitia border (MAb) in human coronary artery in Intravascular Ultrasound (IVUS) images. A robust border detection is achieved by means of a holistic interpretation of the detection problem where the target object, i.e. the media layer, is considered as part of the whole vessel in the image and all the relationships between tissues are learnt. A fairly general framework exploiting multi-class tissue characterization as well as contextual information on the morphology and the appearance of the tissues is presented. The methodology is (i) validated through an exhaustive comparison with both Inter-observer variability on two challenging databases and (ii) compared with state-of-the-art methods for the detection of the MAb in IVUS. The obtained averaged values for the mean radial distance and the percentage of area difference are 0.211 mm and 10.1%, respectively. The applicability of the proposed methodology to clinical practice is also discussed. | ||||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPG2012 | Serial | 1995 | ||
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| Author | Aura Hernandez-Sabate; Debora Gil; Albert Teis | ||||
| Title |
How Do Conservation Laws Define a Motion Suppression Score in In-Vivo Ivus Sequences? | Type | Conference Article | ||
| Year | 2007 | Publication | Proc. IEEE Ultrasonics Symp | Abbreviated Journal | |
| Volume | Issue | Pages | 2231-2234 | ||
| Keywords | validation standards; IVUS motion compensation; conservation laws. | ||||
| Abstract | Evaluation of arterial tissue biomechanics for diagnosis and treatment of cardiovascular diseases is an active research field in the biomedical imaging processing area. IntraVascular UltraSound (IVUS) is a unique tool for such assessment since it reflects tissue morphology and deformation. A proper quantification and visualization of both properties is hindered by vessel structures misalignments introduced by cardiac dynamics. This has encouraged development of IVUS motion compensation techniques. However, there is a lack of an objective evaluation of motion reduction ensuring a reliable clinical application This work reports a novel score, the Conservation of Density Rate (CDR), for validation of motion compensation in in-vivo pullbacks. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases. | ||||
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| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ HTG2007 | Serial | 1550 | ||
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