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Author (down) Xavier Soria; Angel Sappa; Patricio Humanante; Arash Akbarinia edit  url
openurl 
  Title Dense extreme inception network for edge detection Type Journal Article
  Year 2023 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 139 Issue Pages 109461  
  Keywords  
  Abstract Edge detection is the basis of many computer vision applications. State of the art predominantly relies on deep learning with two decisive factors: dataset content and network architecture. Most of the publicly available datasets are not curated for edge detection tasks. Here, we address this limitation. First, we argue that edges, contours and boundaries, despite their overlaps, are three distinct visual features requiring separate benchmark datasets. To this end, we present a new dataset of edges. Second, we propose a novel architecture, termed Dense Extreme Inception Network for Edge Detection (DexiNed), that can be trained from scratch without any pre-trained weights. DexiNed outperforms other algorithms in the presented dataset. It also generalizes well to other datasets without any fine-tuning. The higher quality of DexiNed is also perceptually evident thanks to the sharper and finer edges it outputs.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MSIAU Approved no  
  Call Number Admin @ si @ SSH2023 Serial 3982  
Permanent link to this record
 

 
Author (down) Xavier Soria; Angel Sappa; Arash Akbarinia edit   pdf
openurl 
  Title Multispectral Single-Sensor RGB-NIR Imaging: New Challenges and Opportunities Type Conference Article
  Year 2017 Publication 7th International Conference on Image Processing Theory, Tools & Applications Abbreviated Journal  
  Volume Issue Pages  
  Keywords Color restoration; Neural networks; Singlesensor cameras; Multispectral images; RGB-NIR dataset  
  Abstract Multispectral images captured with a single sensor camera have become an attractive alternative for numerous computer vision applications. However, in order to fully exploit their potentials, the color restoration problem (RGB representation) should be addressed. This problem is more evident in outdoor scenarios containing vegetation, living beings, or specular materials. The problem of color distortion emerges from the sensitivity of sensors due to the overlap of visible and near infrared spectral bands. This paper empirically evaluates the variability of the near infrared (NIR) information with respect to the changes of light throughout the day. A tiny neural network is proposed to restore the RGB color representation from the given RGBN (Red, Green, Blue, NIR) images. In order to evaluate the proposed algorithm, different experiments on a RGBN outdoor dataset are conducted, which include various challenging cases. The obtained result shows the challenge and the importance of addressing color restoration in single sensor multispectral images.  
  Address Montreal; Canada; November 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference IPTA  
  Notes NEUROBIT; MSIAU; 600.122 Approved no  
  Call Number Admin @ si @ SSA2017 Serial 3074  
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Author (down) Xavier Soria; Angel Sappa edit   pdf
openurl 
  Title Improving Edge Detection in RGB Images by Adding NIR Channel Type Conference Article
  Year 2018 Publication 14th IEEE International Conference on Signal Image Technology & Internet Based System Abbreviated Journal  
  Volume Issue Pages  
  Keywords Edge detection; Contour detection; VGG; CNN; RGB-NIR; Near infrared images  
  Abstract The edge detection is yet a critical problem in many computer vision and image processing tasks. The manuscript presents an Holistically-Nested Edge Detection based approach to study the inclusion of Near-Infrared in the Visible spectrum
images. To do so, a Single Sensor based dataset has been acquired in the range of 400nm to 1100nm wavelength spectral band. Prominent results have been obtained even when the ground truth (annotated edge-map) is based in the visible wavelength spectrum.
 
  Address Las Palmas de Gran Canaria; November 2018  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SITIS  
  Notes MSIAU; 600.122 Approved no  
  Call Number Admin @ si @ SoS2018 Serial 3192  
Permanent link to this record
 

 
Author (down) Xavier Soria edit  isbn
openurl 
  Title Single sensor multi-spectral imaging Type Book Whole
  Year 2019 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The image sensor, nowadays, is rolling the smartphone industry. While some phone brands explore equipping more image sensors, others, like Google, maintain their smartphones with just one sensor; but this sensor is equipped with Deep Learning to enhance the image quality. However, what all brands agree on is the need to research new image sensors; for instance, in 2015 Omnivision and PixelTeq presented new CMOS based image sensors defined as multispectral Single Sensor Camera (SSC), which are capable of capturing multispectral bands. This dissertation presents the benefits of using a multispectral SSCs that, as aforementioned, simultaneously acquires images in the visible and near-infrared (NIR) bands. The principal benefits while addressing problems related to image bands in the spectral range of 400 to 1100 nanometers, there are cost reductions in the hardware and software setup because only one SSC is needed instead of two, and the images alignment are not required any more. Concerning to the NIR spectrum, many works in literature have proven the benefits of working with NIR to enhance RGB images (e.g., image enhancement, remove shadows, dehazing, etc.). In spite of the advantage of using SSC (e.g., low latency), there are some drawback to be solved. One of this drawback corresponds to the nature of the silicon-based sensor, which in addition to capture the RGB image, when the infrared cut off filter is not installed it also acquires NIR information into the visible image. This phenomenon is called RGB and NIR crosstalking. This thesis firstly faces this problem in challenging images and then it shows the benefit of using multispectral images in the edge detection task.
The RGB color restoration from RGBN image is the topic tackled in RGB and NIR crosstalking. Even though in the literature a set of processes have been proposed to face this issue, in this thesis novel approaches, based on DL, are proposed to subtract the additional NIR included in the RGB channel. More precisely, an Artificial Neural Network (NN) and two Convolutional Neural Network (CNN) models are proposed. As the DL based models need a dataset with a large collection of image pairs, a large dataset is collected to address the color restoration. The collected images are from challenging scenes where the sunlight radiation is sufficient to give absorption/reflectance properties to the considered scenes. An extensive evaluation has been conducted on the CNN models, differences from most of the restored images are almost imperceptible to the human eye. The next proposal of the thesis is the validation of the usage of SSC images in the edge detection task. Three methods based on CNN have been proposed. While the first one is based on the most used model, holistically-nested edge detection (HED) termed as multispectral HED (MS-HED), the other two have been proposed observing the drawbacks of MS-HED. These two novel architectures have been designed from scratch (training from scratch); after the first architecture is validated in the visible domain a slight redesign is proposed to tackle the multispectral domain. Again, another dataset is collected to face this problem with SSCs. Even though edge detection is confronted in the multispectral domain, its qualitative and quantitative evaluation demonstrates the generalization in other datasets used for edge detection, improving state-of-the-art results.
 
  Address September 2019  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Angel Sappa  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-948531-9-7 Medium  
  Area Expedition Conference  
  Notes MSIAU; 600.122 Approved no  
  Call Number Admin @ si @ Sor2019 Serial 3391  
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Author (down) Xavier Roca; X. Binefa; Jordi Vitria edit  openurl
  Title A New Autofocus Algorithm for Cytological Tissue in a Microscopy Environment. Type Miscellaneous
  Year 1998 Publication Optical Engineering. Abbreviated Journal  
  Volume Issue Pages  
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  Address  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes OR;ISE;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RBV1998 Serial 16  
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Author (down) Xavier Roca; X. Binefa; Jordi Vitria edit  openurl
  Title A New Accomodation Algorithm for a Microscopy Environment. Type Miscellaneous
  Year 1997 Publication VII National Symposium on Pattern Recognition and image Analysis. Vol. 2, pp. 66–67. Abbreviated Journal  
  Volume Issue Pages  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;ISE;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RBV1997 Serial 37  
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Author (down) Xavier Roca; X. Binefa; Jordi Vitria edit  openurl
  Title Multiscale Structure Extraction using Morphological Tools. Applications to Edge Detection and to Depth Perception. Type Miscellaneous
  Year 1993 Publication Technical Workshop on Mathematical Morphology and its Applications to Signal Processing. Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;ISE;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RBV1993 Serial 247  
Permanent link to this record
 

 
Author (down) Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva edit  openurl
  Title Visual behaviours for binocular navigation with autonomous systems. Type Miscellaneous
  Year 1999 Publication Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Bilbao  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;ISE;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RVV1999a Serial 13  
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Author (down) Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva edit  openurl
  Title Gaze control in a binocular robot systems Type Miscellaneous
  Year 1999 Publication Abbreviated Journal  
  Volume Issue Pages  
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  Address Barcelona  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;ISE;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RVV1999b Serial 41  
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Author (down) Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva edit  openurl
  Title Visual behaviours for binocular navigation with autonomous systems. Type Miscellaneous
  Year 2000 Publication Pattern Recognition and Applications, IOS Press, 134–143. Abbreviated Journal  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;ISE;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RVV2000 Serial 245  
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Author (down) Xavier Roca; Jordi Vitria edit  openurl
  Title Multiscale Structure Extraction using Morphological Tools. Applications to Edge Detection. Type Miscellaneous
  Year 1993 Publication SPIE International Symposium on Optical Instrumentation and Applied Science (Conference on image Algebra and Morphological image Processing IV). Abbreviated Journal  
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  Address San Diego; CA; USA  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;ISE;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RoV1993 Serial 176  
Permanent link to this record
 

 
Author (down) Xavier Perez; Cecilio Angulo; Sergio Escalera edit  doi
isbn  openurl
  Title Biologically Inspired Path Execution Using SURF Flow in Robot Navigation Type Conference Article
  Year 2011 Publication 11th International Work Conference on Artificial Neural Networks Abbreviated Journal  
  Volume II Issue Pages 581--588  
  Keywords  
  Abstract An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo.  
  Address Malaga  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21497-4 Medium  
  Area Expedition Conference IWANN  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ PAE2011b Serial 1773  
Permanent link to this record
 

 
Author (down) Xavier Perez Sala; Sergio Escalera; Cecilio Angulo; Jordi Gonzalez edit   pdf
doi  openurl
  Title A survey on model based approaches for 2D and 3D visual human pose recovery Type Journal Article
  Year 2014 Publication Sensors Abbreviated Journal SENS  
  Volume 14 Issue 3 Pages 4189-4210  
  Keywords human pose recovery; human body modelling; behavior analysis; computer vision  
  Abstract Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a general taxonomy to group model based approaches for Human Pose Recovery, which is composed of five main modules: appearance, viewpoint, spatial relations, temporal consistence, and behavior. Subsequently, a methodological comparison is performed following the proposed taxonomy, evaluating current SoA approaches in the aforementioned five group categories. As a result of this comparison, we discuss the main advantages and drawbacks of the reviewed literature.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA; ISE; 600.046; 600.063; 600.078;MILAB Approved no  
  Call Number Admin @ si @ PEA2014 Serial 2443  
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Author (down) Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo edit   pdf
doi  openurl
  Title Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models Type Book Chapter
  Year 2012 Publication Vision Robotics: Technologies for Machine Learning and Vision Applications Abbreviated Journal  
  Volume Issue 2 Pages 23-42  
  Keywords  
  Abstract Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis.  
  Address  
  Corporate Author Thesis  
  Publisher IGI-Global Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ PIE2012 Serial 2064  
Permanent link to this record
 

 
Author (down) Xavier Perez Sala; Fernando De la Torre; Laura Igual; Sergio Escalera; Cecilio Angulo edit   pdf
doi  openurl
  Title Subspace Procrustes Analysis Type Conference Article
  Year 2014 Publication ECCV Workshop on ChaLearn Looking at People Abbreviated Journal  
  Volume 8925 Issue Pages 654-668  
  Keywords  
  Abstract Procrustes Analysis (PA) has been a popular technique to align and build 2-D statistical models of shapes. Given a set of 2-D shapes PA is applied to remove rigid transformations. Then, a non-rigid 2-D model is computed by modeling (e.g., PCA) the residual. Although PA has been widely used, it has several limitations for modeling 2-D shapes: occluded landmarks and missing data can result in local minima solutions, and there is no guarantee that the 2-D shapes provide a uniform sampling of the 3-D space of rotations for the object. To address previous issues, this paper proposes Subspace PA (SPA). Given several instances of a 3-D object, SPA computes the mean and a 2-D subspace that can simultaneously model all rigid and non-rigid deformations of the 3-D object. We propose a discrete (DSPA) and continuous (CSPA) formulation for SPA, assuming that 3-D samples of an object are provided. DSPA extends the traditional PA, and produces unbiased 2-D models by uniformly sampling di erent views of the 3-D object. CSPA provides a continuous approach to uniformly sample the space of 3-D rotations, being more ecient in space and time. Experiments using SPA to learn 2-D models of bodies from motion capture data illustrate the bene ts of our approach.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECCVW  
  Notes OR; HuPBA;MILAB Approved no  
  Call Number Admin @ si @ PTI2014 Serial 2539  
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