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Author |
Michael Teutsch; Angel Sappa; Riad I. Hammoud |
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Title |
Cross-Spectral Image Processing |
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Book Chapter |
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Year |
2022 |
Publication |
Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision |
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23-34 |
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Although this book is on IR computer vision and its main focus lies on IR image and video processing and analysis, a special attention is dedicated to cross-spectral image processing due to the increasing number of publications and applications in this domain. In these cross-spectral frameworks, IR information is used together with information from other spectral bands to tackle some specific problems by developing more robust solutions. Tasks considered for cross-spectral processing are for instance dehazing, segmentation, vegetation index estimation, or face recognition. This increasing number of applications is motivated by cross- and multi-spectral camera setups available already on the market like for example smartphones, remote sensing multispectral cameras, or multi-spectral cameras for automotive systems or drones. In this chapter, different cross-spectral image processing techniques will be reviewed together with possible applications. Initially, image registration approaches for the cross-spectral case are reviewed: the registration stage is the first image processing task, which is needed to align images acquired by different sensors within the same reference coordinate system. Then, recent cross-spectral image colorization approaches, which are intended to colorize infrared images for different applications are presented. Finally, the cross-spectral image enhancement problem is tackled by including guided super resolution techniques, image dehazing approaches, cross-spectral filtering and edge detection. Figure 3.1 illustrates cross-spectral image processing stages as well as their possible connections. Table 3.1 presents some of the available public cross-spectral datasets generally used as reference data to evaluate cross-spectral image registration, colorization, enhancement, or exploitation results. |
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Springer |
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SLCV |
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978-3-031-00698-2 |
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MSIAU; MACO |
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no |
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Admin @ si @ TSH2022b |
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3805 |
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Author |
Michael Teutsch; Angel Sappa; Riad I. Hammoud |
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Title |
Detection, Classification, and Tracking |
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Book Chapter |
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Year |
2022 |
Publication |
Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision |
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35-58 |
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Automatic image and video exploitation or content analysis is a technique to extract higher-level information from a scene such as objects, behavior, (inter-)actions, environment, or even weather conditions. The relevant information is assumed to be contained in the two-dimensional signal provided in an image (width and height in pixels) or the three-dimensional signal provided in a video (width, height, and time). But also intermediate-level information such as object classes [196], locations [197], or motion [198] can help applications to fulfill certain tasks such as intelligent compression [199], video summarization [200], or video retrieval [201]. Usually, videos with their temporal dimension are a richer source of data compared to single images [202] and thus certain video content can be extracted from videos only such as object motion or object behavior. Often, machine learning or nowadays deep learning techniques are utilized to model prior knowledge about object or scene appearance using labeled training samples [203, 204]. After a learning phase, these models are then applied in real world applications, which is called inference. |
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Springer |
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SLCV |
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978-3-031-00698-2 |
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MSIAU; MACO |
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Admin @ si @ TSH2022c |
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3806 |
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Author |
Michael Teutsch; Angel Sappa; Riad I. Hammoud |
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Title |
Image and Video Enhancement |
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Book Chapter |
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Year |
2022 |
Publication |
Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision |
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9-21 |
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Image and video enhancement aims at improving the signal quality relative to imaging artifacts such as noise and blur or atmospheric perturbations such as turbulence and haze. It is usually performed in order to assist humans in analyzing image and video content or simply to present humans visually appealing images and videos. However, image and video enhancement can also be used as a preprocessing technique to ease the task and thus improve the performance of subsequent automatic image content analysis algorithms: preceding dehazing can improve object detection as shown by [23] or explicit turbulence modeling can improve moving object detection as discussed by [24]. But it remains an open question whether image and video enhancement should rather be performed explicitly as a preprocessing step or implicitly for example by feeding affected images directly to a neural network for image content analysis like object detection [25]. Especially for real-time video processing at low latency it can be better to handle image perturbation implicitly in order to minimize the processing time of an algorithm. This can be achieved by making algorithms for image content analysis robust or even invariant to perturbations such as noise or blur. Additionally, mistakes of an individual preprocessing module can obviously affect the quality of the entire processing pipeline. |
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Springer |
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SLCV |
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MSIAU; MACO |
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no |
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Admin @ si @ TSH2022a |
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3807 |
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Author |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) |
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Title |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 |
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Book Whole |
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Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. |
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13639 |
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ICFHR 2022, Hyderabad, India, December 4–7, 2022 |
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Springer |
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Utkarsh Porwal; Alicia Fornes; Faisal Shafait |
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LNCS |
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978-3-031-21648-0 |
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ICFHR |
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DAG |
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no |
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Admin @ si @ PFS2022 |
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3809 |
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Author |
Jorge Charco; Angel Sappa; Boris X. Vintimilla; Henry Velesaca |
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Title |
Human Body Pose Estimation in Multi-view Environments |
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Book Chapter |
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Year |
2022 |
Publication |
ICT Applications for Smart Cities. Intelligent Systems Reference Library |
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Volume |
224 |
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Pages |
79-99 |
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Abstract |
This chapter tackles the challenging problem of human pose estimation in multi-view environments to handle scenes with self-occlusions. The proposed approach starts by first estimating the camera pose—extrinsic parameters—in multi-view scenarios; due to few real image datasets, different virtual scenes are generated by using a special simulator, for training and testing the proposed convolutional neural network based approaches. Then, these extrinsic parameters are used to establish the relation between different cameras into the multi-view scheme, which captures the pose of the person from different points of view at the same time. The proposed multi-view scheme allows to robustly estimate human body joints’ position even in situations where they are occluded. This would help to avoid possible false alarms in behavioral analysis systems of smart cities, as well as applications for physical therapy, safe moving assistance for the elderly among other. The chapter concludes by presenting experimental results in real scenes by using state-of-the-art and the proposed multi-view approaches. |
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September 2022 |
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Springer |
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ISRL |
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978-3-031-06306-0 |
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MSIAU; MACO |
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no |
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Admin @ si @ CSV2022b |
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3810 |
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Author |
Henry Velesaca; Patricia Suarez; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez; Angel Morera |
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Title |
Video Analytics in Urban Environments: Challenges and Approaches |
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Book Chapter |
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Year |
2022 |
Publication |
ICT Applications for Smart Cities |
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Volume |
224 |
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Pages |
101-121 |
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This chapter reviews state-of-the-art approaches generally present in the pipeline of video analytics on urban scenarios. A typical pipeline is used to cluster approaches in the literature, including image preprocessing, object detection, object classification, and object tracking modules. Then, a review of recent approaches for each module is given. Additionally, applications and datasets generally used for training and evaluating the performance of these approaches are included. This chapter does not pretend to be an exhaustive review of state-of-the-art video analytics in urban environments but rather an illustration of some of the different recent contributions. The chapter concludes by presenting current trends in video analytics in the urban scenario field. |
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September 2022 |
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Springer |
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ISRL |
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978-3-031-06306-0 |
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MSIAU; MACO |
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no |
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Admin @ si @ VSC2022 |
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3811 |
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Permanent link to this record |
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Author |
Angel Sappa (ed) |
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Title |
ICT Applications for Smart Cities |
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Book Whole |
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Year |
2022 |
Publication |
ICT Applications for Smart Cities |
Abbreviated Journal |
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Volume |
224 |
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Keywords |
Computational Intelligence; Intelligent Systems; Smart Cities; ICT Applications; Machine Learning; Pattern Recognition; Computer Vision; Image Processing |
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Abstract |
Part of the book series: Intelligent Systems Reference Library (ISRL)
This book is the result of four-year work in the framework of the Ibero-American Research Network TICs4CI funded by the CYTED program. In the following decades, 85% of the world's population is expected to live in cities; hence, urban centers should be prepared to provide smart solutions for problems ranging from video surveillance and intelligent mobility to the solid waste recycling processes, just to mention a few. More specifically, the book describes underlying technologies and practical implementations of several successful case studies of ICTs developed in the following smart city areas:
• Urban environment monitoring
• Intelligent mobility
• Waste recycling processes
• Video surveillance
• Computer-aided diagnose in healthcare systems
• Computer vision-based approaches for efficiency in production processes
The book is intended for researchers and engineers in the field of ICTs for smart cities, as well as to anyone who wants to know about state-of-the-art approaches and challenges on this field. |
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September 2022 |
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Springer |
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Editor |
Angel Sappa |
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ISRL |
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978-3-031-06306-0 |
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MSIAU; MACO |
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no |
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Call Number |
Admin @ si @ Sap2022 |
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3812 |
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Author |
Victoria Ruiz; Angel Sanchez; Jose F. Velez; Bogdan Raducanu |
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Title |
Waste Classification with Small Datasets and Limited Resources |
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Book Chapter |
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Year |
2022 |
Publication |
ICT Applications for Smart Cities. Intelligent Systems Reference Library |
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224 |
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185-203 |
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Automatic waste recycling has become a very important societal challenge nowadays, raising people’s awareness for a cleaner environment and a more sustainable lifestyle. With the transition to Smart Cities, and thanks to advanced ICT solutions, this problem has received a new impulse. The waste recycling focus has shifted from general waste treating facilities to an individual responsibility, where each person should become aware of selective waste separation. The surge of the mobile devices, accompanied by a significant increase in computation power, has potentiated and facilitated this individual role. An automated image-based waste classification mechanism can help with a more efficient recycling and a reduction of contamination from residuals. Despite the good results achieved with the deep learning methodologies for this task, the Achille’s heel is that they require large neural networks which need significant computational resources for training and therefore are not suitable for mobile devices. To circumvent this apparently intractable problem, we will rely on knowledge distillation in order to transfer the network’s knowledge from a larger network (called ‘teacher’) to a smaller, more compact one, (referred as ‘student’) and thus making it possible the task of image classification on a device with limited resources. For evaluation, we considered as ‘teachers’ large architectures such as InceptionResNet or DenseNet and as ‘students’, several configurations of the MobileNets. We used the publicly available TrashNet dataset to demonstrate that the distillation process does not significantly affect system’s performance (e.g. classification accuracy) of the student network. |
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September 2022 |
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Springer |
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ISRL |
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978-3-031-06306-0 |
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LAMP |
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no |
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Call Number |
Admin @ si @ |
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3813 |
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Author |
Jaume Garcia; Debora Gil; Aura Hernandez-Sabate |
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Title |
Endowing Canonical Geometries to Cardiac Structures |
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Book Chapter |
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2010 |
Publication |
Statistical Atlases And Computational Models Of The Heart |
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6364 |
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124-133 |
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Abstract |
International conference on Cardiac electrophysiological simulation challenge
In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view. |
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Springer Berlin / Heidelberg |
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Camara, O.; Pop, M.; Rhode, K.; Sermesant, M.; Smith, N.; Young, A. |
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Lecture Notes in Computer Science |
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LNCS |
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IAM |
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IAM @ iam @ GGH2010b |
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1515 |
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Author |
Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil |
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Title |
Suppression of IVUS Image Rotation. A Kinematic Approach |
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Book Chapter |
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2005 |
Publication |
Functional Imaging and Modeling of the Heart |
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LNCS |
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3504 |
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889-892 |
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IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology. |
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Springer Berlin / Heidelberg |
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Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica |
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Lecture Notes in Computer Science |
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LNCS |
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3504 |
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IAM;MILAB |
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IAM @ iam @ RRR2005 |
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1645 |
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Author |
Salim Jouili; Salvatore Tabbone; Ernest Valveny |
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Title |
Comparing Graph Similarity Measures for Graphical Recognition |
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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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37-48 |
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In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique. |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG |
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no |
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Admin @ si @ JTV2010 |
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2404 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
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Title |
Improving Fuzzy Multilevel Graph Embedding through Feature Selection Technique |
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Conference Article |
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2012 |
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Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
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7626 |
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243-253 |
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Graphs are the most powerful, expressive and convenient data structures but there is a lack of efficient computational tools and algorithms for processing them. The embedding of graphs into numeric vector spaces permits them to access the state-of-the-art computational efficient statistical models and tools. In this paper we take forward our work on explicit graph embedding and present an improvement to our earlier proposed method, named “fuzzy multilevel graph embedding – FMGE”, through feature selection technique. FMGE achieves the embedding of attributed graphs into low dimensional vector spaces by performing a multilevel analysis of graphs and extracting a set of global, structural and elementary level features. Feature selection permits FMGE to select the subset of most discriminating features and to discard the confusing ones for underlying graph dataset. Experimental results for graph classification experimentation on IAM letter, GREC and fingerprint graph databases, show improvement in the performance of FMGE. |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-34165-6 |
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SSPR&SPR |
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DAG |
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no |
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Admin @ si @ LRL2012 |
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2381 |
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Author |
Carlo Gatta; Juan Diego Gomez; Francesco Ciompi; Oriol Rodriguez-Leor; Petia Radeva |
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Title |
Toward robust myocardial blush grade estimation in contrast angiography |
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Conference Article |
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2009 |
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4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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249–256 |
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Abstract |
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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Address |
Póvoa de Varzim, Portugal |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-02171-8 |
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Conference |
IbPRIA |
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Notes |
MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ GGC2009 |
Serial |
1161 |
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Author |
Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Carlo Gatta; Angel Serrano; Petia Radeva |
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Title |
Enhancing In-Vitro IVUS Data for Tissue Characterization |
Type |
Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
5524 |
Issue |
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Pages |
241–248 |
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Abstract |
Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%. |
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Address |
Póvoa de Varzim, Portugal |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-02171-8 |
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Expedition |
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Conference |
IbPRIA |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ CPR2009a |
Serial |
1162 |
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Author |
Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; Horst Bunke |
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Title |
A Recursive Embedding Approach to Median Graph Computation |
Type |
Conference Article |
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Year |
2009 |
Publication |
7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition |
Abbreviated Journal |
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Volume |
5534 |
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Pages |
113–123 |
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Keywords |
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Abstract |
The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches. |
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Address |
Venice, Italy |
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Publisher |
Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-02123-7 |
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Conference |
GBR |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ FKV2009 |
Serial |
1173 |
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Permanent link to this record |