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Author | Aura Hernandez-Sabate; Meritxell Joanpere; Nuria Gorgorio; Lluis Albarracin | ||||
Title | Mathematics learning opportunities when playing a Tower Defense Game | Type | Journal | ||
Year | 2015 | Publication | International Journal of Serious Games | Abbreviated Journal | IJSG |
Volume | 2 | Issue | 4 | Pages | 57-71 |
Keywords | Tower Defense game; learning opportunities; mathematics; problem solving; game design | ||||
Abstract | A qualitative research study is presented herein with the purpose of identifying mathematics learning opportunities in students between 10 and 12 years old while playing a commercial version of a Tower Defense game. These learning opportunities are understood as mathematicisable moments of the game and involve the establishment of relationships between the game and mathematical problem solving. Based on the analysis of these mathematicisable moments, we conclude that the game can promote problem-solving processes and learning opportunities that can be associated with different mathematical contents that appears in mathematics curricula, thought it seems that teacher or new game elements might be needed to facilitate the processes. | ||||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ HJG2015 | Serial | 2730 | ||
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Author | Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; I.Araujo ; Maria Lopez Ceron; J.Llach; F. Javier Sanchez | ||||
Title | Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps | Type | Conference Article | ||
Year | 2015 | Publication | Proceedings of 23 United European- UEG Week 2015 | Abbreviated Journal | |
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Area | Expedition | Conference | UEG | ||
Notes | MV; IAM; 600.075;SIAI | Approved | no | ||
Call Number | Admin @ si @ FBR2015 | Serial | 2732 | ||
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Author | Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal | ||||
Title | 3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos | Type | Book Chapter | ||
Year | 2015 | Publication | Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 | Abbreviated Journal | |
Volume | 9515 | Issue | Pages | 140-152 | |
Keywords | Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds | ||||
Abstract | Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response. Spatio-temporal stability is achieved by extracting 3D watershed regions on the temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection. |
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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Area | Expedition | Conference | CARE | ||
Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | Admin @ si @ GSF2015 | Serial | 2733 | ||
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Author | Mariella Dimiccoli; Jean-Pascal Jacob; Lionel Moisan | ||||
Title | Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach | Type | Journal Article | ||
Year | 2016 | Publication | Journal of Machine Vision and Applications | Abbreviated Journal | MVAP |
Volume | 27 | Issue | Pages | 511-527 | |
Keywords | particle detection; particle tracking; a-contrario approach; time-lapse fluorescence imaging | ||||
Abstract | In this work, we propose a probabilistic approach for the detection and the
tracking of particles on biological images. In presence of very noised and poor quality data, particles and trajectories can be characterized by an a-contrario model, that estimates the probability of observing the structures of interest in random data. This approach, first introduced in the modeling of human visual perception and then successfully applied in many image processing tasks, leads to algorithms that do not require a previous learning stage, nor a tedious parameter tuning and are very robust to noise. Comparative evaluations against a well established baseline show that the proposed approach outperforms the state of the art. |
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Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @ DJM2016 | Serial | 2735 | ||
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Author | Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich | ||||
Title | DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition | Type | Conference Article | ||
Year | 2015 | Publication | Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II | Abbreviated Journal | |
Volume | 9475 | Issue | Pages | 463-473 | |
Keywords | Projector-camera systems; Feature descriptors; Object recognition | ||||
Abstract | Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. | ||||
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Publisher | Springer International Publishing | 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 | 978-3-319-27862-9 | Medium | |
Area | Expedition | Conference | ISVC | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ SMG2015 | Serial | 2736 | ||
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Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
Title | Multi-face tracking by extended bag-of-tracklets in egocentric photo-streams | Type | Journal Article | ||
Year | 2016 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 149 | Issue | Pages | 146-156 | |
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Abstract | Wearable cameras offer a hands-free way to record egocentric images of daily experiences, where social events are of special interest. The first step towards detection of social events is to track the appearance of multiple persons involved in them. In this paper, we propose a novel method to find correspondences of multiple faces in low temporal resolution egocentric videos acquired through a wearable camera. This kind of photo-stream imposes additional challenges to the multi-tracking problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution, abrupt changes in the field of view, in illumination condition and in the target location are highly frequent. To overcome such difficulties, we propose a multi-face tracking method that generates a set of tracklets through finding correspondences along the whole sequence for each detected face and takes advantage of the tracklets redundancy to deal with unreliable ones. Similar tracklets are grouped into the so called extended bag-of-tracklets (eBoT), which is aimed to correspond to a specific person. Finally, a prototype tracklet is extracted for each eBoT, where the occurred occlusions are estimated by relying on a new measure of confidence. We validated our approach over an extensive dataset of egocentric photo-streams and compared it to state of the art methods, demonstrating its effectiveness and robustness. | ||||
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Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @ ADR2016b | Serial | 2742 | ||
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Author | Hugo Jair Escalante; Victor Ponce; Sergio Escalera; Xavier Baro; Alicia Morales-Reyes; Jose Martinez-Carranza | ||||
Title | Evolving weighting schemes for the Bag of Visual Words | Type | Journal Article | ||
Year | 2017 | Publication | Neural Computing and Applications | Abbreviated Journal | Neural Computing and Applications |
Volume | 28 | Issue | 5 | Pages | 925–939 |
Keywords | Bag of Visual Words; Bag of features; Genetic programming; Term-weighting schemes; Computer vision | ||||
Abstract | The Bag of Visual Words (BoVW) is an established representation in computer vision. Taking inspiration from text mining, this representation has proved
to be very effective in many domains. However, in most cases, standard term-weighting schemes are adopted (e.g.,term-frequency or TF-IDF). It remains open the question of whether alternative weighting schemes could boost the performance of methods based on BoVW. More importantly, it is unknown whether it is possible to automatically learn and determine effective weighting schemes from scratch. This paper brings some light into both of these unknowns. On the one hand, we report an evaluation of the most common weighting schemes used in text mining, but rarely used in computer vision tasks. Besides, we propose an evolutionary algorithm capable of automatically learning weighting schemes for computer vision problems. We report empirical results of an extensive study in several computer vision problems. Results show the usefulness of the proposed method. |
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Publisher | Place of Publication | Editor | Springer | ||
Language | Summary Language | Original Title | |||
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Notes | HUPBA;MV; no menciona | Approved | no | ||
Call Number | Admin @ si @ EPE2017 | Serial | 2743 | ||
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Author | Onur Ferhat; Fernando Vilariño | ||||
Title | Low Cost Eye Tracking: The Current Panorama | Type | Journal Article | ||
Year | 2016 | Publication | Computational Intelligence and Neuroscience | Abbreviated Journal | CIN |
Volume | Issue | Pages | Article ID 8680541 | ||
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Abstract | Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools. | ||||
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Notes | MV; 605.103; 600.047; 600.097;SIAI | Approved | no | ||
Call Number | Admin @ si @ FeV2016 | Serial | 2744 | ||
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Author | Maria Oliver; G. Haro; Mariella Dimiccoli; B. Mazin; C. Ballester | ||||
Title | A Computational Model for Amodal Completion | Type | Journal Article | ||
Year | 2016 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
Volume | 56 | Issue | 3 | Pages | 511–534 |
Keywords | Perception; visual completion; disocclusion; Bayesian model;relatability; Euler elastica | ||||
Abstract | This paper presents a computational model to recover the most likely interpretation
of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler's elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler's elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling. |
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Notes | MILAB; 601.235 | Approved | no | ||
Call Number | Admin @ si @ OHD2016b | Serial | 2745 | ||
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Author | David Sanchez-Mendoza; David Masip; Agata Lapedriza | ||||
Title | Emotion recognition from mid-level features | Type | Journal Article | ||
Year | 2015 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 67 | Issue | Part 1 | Pages | 66–74 |
Keywords | Facial expression; Emotion recognition; Action units; Computer vision | ||||
Abstract | In this paper we present a study on the use of Action Units as mid-level features for automatically recognizing basic and subtle emotions. We propose a representation model based on mid-level facial muscular movement features. We encode these movements dynamically using the Facial Action Coding System, and propose to use these intermediate features based on Action Units (AUs) to classify emotions. AUs activations are detected fusing a set of spatiotemporal geometric and appearance features. The algorithm is validated in two applications: (i) the recognition of 7 basic emotions using the publicly available Cohn-Kanade database, and (ii) the inference of subtle emotional cues in the Newscast database. In this second scenario, we consider emotions that are perceived cumulatively in longer periods of time. In particular, we Automatically classify whether video shoots from public News TV channels refer to Good or Bad news. To deal with the different video lengths we propose a Histogram of Action Units and compute it using a sliding window strategy on the frame sequences. Our approach achieves accuracies close to human perception. | ||||
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Publisher | Elsevier B.V. | Place of Publication | Editor | ||
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ISSN | 0167-8655 | ISBN | Medium | ||
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Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ SML2015 | Serial | 2746 | ||
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Author | C. Alejandro Parraga; Arash Akbarinia | ||||
Title | NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization | Type | Journal Article | ||
Year | 2016 | Publication | PLoS One | Abbreviated Journal | Plos |
Volume | 11 | Issue | 3 | Pages | e0149538 |
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Abstract | The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms. | ||||
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Notes | NEUROBIT; 600.068 | Approved | no | ||
Call Number | Admin @ si @ PaA2016a | Serial | 2747 | ||
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Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
Title | On the completeness of feature-driven maximally stable extremal regions | Type | Journal Article | ||
Year | 2016 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 74 | Issue | Pages | 9-16 | |
Keywords | Local features; Completeness; Maximally Stable Extremal Regions | ||||
Abstract | By definition, local image features provide a compact representation of the image in which most of the image information is preserved. This capability offered by local features has been overlooked, despite being relevant in many application scenarios. In this paper, we analyze and discuss the performance of feature-driven Maximally Stable Extremal Regions (MSER) in terms of the coverage of informative image parts (completeness). This type of features results from an MSER extraction on saliency maps in which features related to objects boundaries or even symmetry axes are highlighted. These maps are intended to be suitable domains for MSER detection, allowing this detector to provide a better coverage of informative image parts. Our experimental results, which were based on a large-scale evaluation, show that feature-driven MSER have relatively high completeness values and provide more complete sets than a traditional MSER detection even when sets of similar cardinality are considered. | ||||
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Publisher | Elsevier B.V. | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | 0167-8655 | ISBN | Medium | ||
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Notes | LAMP;MILAB; | Approved | no | ||
Call Number | Admin @ si @ MCG2016 | Serial | 2748 | ||
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Author | Alejandro Gonzalez Alzate; Zhijie Fang; Yainuvis Socarras; Joan Serrat; David Vazquez; Jiaolong Xu; Antonio Lopez | ||||
Title | Pedestrian Detection at Day/Night Time with Visible and FIR Cameras: A Comparison | Type | Journal Article | ||
Year | 2016 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 16 | Issue | 6 | Pages | 820 |
Keywords | Pedestrian Detection; FIR | ||||
Abstract | Despite all the significant advances in pedestrian detection brought by computer vision for driving assistance, it is still a challenging problem. One reason is the extremely varying lighting conditions under which such a detector should operate, namely day and night time. Recent research has shown that the combination of visible and non-visible imaging modalities may increase detection accuracy, where the infrared spectrum plays a critical role. The goal of this paper is to assess the accuracy gain of different pedestrian models (holistic, part-based, patch-based) when training with images in the far infrared spectrum. Specifically, we want to compare detection accuracy on test images recorded at day and nighttime if trained (and tested) using (a) plain color images, (b) just infrared images and (c) both of them. In order to obtain results for the last item we propose an early fusion approach to combine features from both modalities. We base the evaluation on a new dataset we have built for this purpose as well as on the publicly available KAIST multispectral dataset. | ||||
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ISSN | 1424-8220 | ISBN | Medium | ||
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Notes | ADAS; 600.085; 600.076; 600.082; 601.281 | Approved | no | ||
Call Number | ADAS @ adas @ GFS2016 | Serial | 2754 | ||
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Author | Egils Avots; M. Daneshmanda; Andres Traumann; Sergio Escalera; G. Anbarjafaria | ||||
Title | Automatic garment retexturing based on infrared information | Type | Journal Article | ||
Year | 2016 | Publication | Computers & Graphics | Abbreviated Journal | CG |
Volume | 59 | Issue | Pages | 28-38 | |
Keywords | Garment Retexturing; Texture Mapping; Infrared Images; RGB-D Acquisition Devices; Shading | ||||
Abstract | This paper introduces a new automatic technique for garment retexturing using a single static image along with the depth and infrared information obtained using the Microsoft Kinect II as the RGB-D acquisition device. First, the garment is segmented out from the image using either the Breadth-First Search algorithm or the semi-automatic procedure provided by the GrabCut method. Then texture domain coordinates are computed for each pixel belonging to the garment using normalised 3D information. Afterwards, shading is applied to the new colours from the texture image. As the main contribution of the proposed method, the latter information is obtained based on extracting a linear map transforming the colour present on the infrared image to that of the RGB colour channels. One of the most important impacts of this strategy is that the resulting retexturing algorithm is colour-, pattern- and lighting-invariant. The experimental results show that it can be used to produce realistic representations, which is substantiated through implementing it under various experimentation scenarios, involving varying lighting intensities and directions. Successful results are accomplished also on video sequences, as well as on images of subjects taking different poses. Based on the Mean Opinion Score analysis conducted on many randomly chosen users, it has been shown to produce more realistic-looking results compared to the existing state-of-the-art methods suggested in the literature. From a wide perspective, the proposed method can be used for retexturing all sorts of segmented surfaces, although the focus of this study is on garment retexturing, and the investigation of the configurations is steered accordingly, since the experiments target an application in the context of virtual fitting rooms. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ ADT2016 | Serial | 2759 | ||
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Author | Katerine Diaz; Aura Hernandez-Sabate; Antonio Lopez | ||||
Title | A reduced feature set for driver head pose estimation | Type | Journal Article | ||
Year | 2016 | Publication | Applied Soft Computing | Abbreviated Journal | ASOC |
Volume | 45 | Issue | Pages | 98-107 | |
Keywords | Head pose estimation; driving performance evaluation; subspace based methods; linear regression | ||||
Abstract | Evaluation of driving performance is of utmost importance in order to reduce road accident rate. Since driving ability includes visual-spatial and operational attention, among others, head pose estimation of the driver is a crucial indicator of driving performance. This paper proposes a new automatic method for coarse and fine head's yaw angle estimation of the driver. We rely on a set of geometric features computed from just three representative facial keypoints, namely the center of the eyes and the nose tip. With these geometric features, our method combines two manifold embedding methods and a linear regression one. In addition, the method has a confidence mechanism to decide if the classification of a sample is not reliable. The approach has been tested using the CMU-PIE dataset and our own driver dataset. Despite the very few facial keypoints required, the results are comparable to the state-of-the-art techniques. The low computational cost of the method and its robustness makes feasible to integrate it in massive consume devices as a real time application. | ||||
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Notes | ADAS; 600.085; 600.076; | Approved | no | ||
Call Number | Admin @ si @ DHL2016 | Serial | 2760 | ||
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