|
Records |
Links |
|
Author |
Ozge Mercanoglu Sincan; Julio C. S. Jacques Junior; Sergio Escalera; Hacer Yalim Keles |
|
|
Title |
ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research |
Type |
Conference Article |
|
Year |
2021 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
3467-3476 |
|
|
Keywords |
|
|
|
Abstract |
The performances of Sign Language Recognition (SLR) systems have improved considerably in recent years. However, several open challenges still need to be solved to allow SLR to be useful in practice. The research in the field is in its infancy in regards to the robustness of the models to a large diversity of signs and signers, and to fairness of the models to performers from different demographics. This work summarises the ChaLearn LAP Large Scale Signer Independent Isolated SLR Challenge, organised at CVPR 2021 with the goal of overcoming some of the aforementioned challenges. We analyse and discuss the challenge design, top winning solutions and suggestions for future research. The challenge attracted 132 participants in the RGB track and 59 in the RGB+Depth track, receiving more than 1.5K submissions in total. Participants were evaluated using a new large-scale multi-modal Turkish Sign Language (AUTSL) dataset, consisting of 226 sign labels and 36,302 isolated sign video samples performed by 43 different signers. Winning teams achieved more than 96% recognition rate, and their approaches benefited from pose/hand/face estimation, transfer learning, external data, fusion/ensemble of modalities and different strategies to model spatio-temporal information. However, methods still fail to distinguish among very similar signs, in particular those sharing similar hand trajectories. |
|
|
Address |
Virtual; June 2021 |
|
|
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 |
CVPRW |
|
|
Notes |
HuPBA; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ MJE2021 |
Serial |
3560 |
|
Permanent link to this record |
|
|
|
|
Author |
Cristina Palmero; Oleg V Komogortsev; Sergio Escalera; Sachin S Talathi |
|
|
Title |
Multi-Rate Sensor Fusion for Unconstrained Near-Eye Gaze Estimation |
Type |
Conference Article |
|
Year |
2023 |
Publication |
Proceedings of the 2023 Symposium on Eye Tracking Research and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1-8 |
|
|
Keywords |
|
|
|
Abstract |
The power requirements of video-oculography systems can be prohibitive for high-speed operation on portable devices. Recently, low-power alternatives such as photosensors have been evaluated, providing gaze estimates at high frequency with a trade-off in accuracy and robustness. Potentially, an approach combining slow/high-fidelity and fast/low-fidelity sensors should be able to exploit their complementarity to track fast eye motion accurately and robustly. To foster research on this topic, we introduce OpenSFEDS, a near-eye gaze estimation dataset containing approximately 2M synthetic camera-photosensor image pairs sampled at 500 Hz under varied appearance and camera position. We also formulate the task of sensor fusion for gaze estimation, proposing a deep learning framework consisting in appearance-based encoding and temporal eye-state dynamics. We evaluate several single- and multi-rate fusion baselines on OpenSFEDS, achieving 8.7% error decrease when tracking fast eye movements with a multi-rate approach vs. a gaze forecasting approach operating with a low-speed sensor alone. |
|
|
Address |
Tubingen; Germany; May 2023 |
|
|
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 |
ETRA |
|
|
Notes |
HUPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ PKE2023 |
Serial |
3923 |
|
Permanent link to this record |
|
|
|
|
Author |
Ana Maria Ares; Jorge Bernal; Maria Jesus Nozal; F. Javier Sanchez; Jose Bernal |
|
|
Title |
Results of the use of Kahoot! gamification tool in a course of Chemistry |
Type |
Conference Article |
|
Year |
2018 |
Publication |
4th International Conference on Higher Education Advances |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1215-1222 |
|
|
Keywords |
|
|
|
Abstract |
The present study examines the use of Kahoot! as a gamification tool to explore mixed learning strategies. We analyze its use in two different groups of a theoretical subject of the third course of the Degree in Chemistry. An empirical-analytical methodology was used using Kahoot! in two different groups of students, with different frequencies. The academic results of these two group of students were compared between them and with those obtained in the previous course, in which Kahoot! was not employed, with the aim of measuring the evolution in the students´ knowledge. The results showed, in all cases, that the use of Kahoot! has led to a significant increase in the overall marks, and in the number of students who passed the subject. Moreover, some differences were also observed in students´ academic performance according to the group. Finally, it can be concluded that the use of a gamification tool (Kahoot!) in a university classroom had generally improved students´ learning and marks, and that this improvement is more prevalent in those students who have achieved a better Kahoot! performance. |
|
|
Address |
Valencia; June 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 |
HEAD |
|
|
Notes |
MV; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ ABN2018 |
Serial |
3246 |
|
Permanent link to this record |
|
|
|
|
Author |
Fei Yang; Kai Wang; Joost Van de Weijer |
|
|
Title |
ScrollNet: DynamicWeight Importance for Continual Learning |
Type |
Conference Article |
|
Year |
2023 |
Publication |
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
3345-3355 |
|
|
Keywords |
|
|
|
Abstract |
The principle underlying most existing continual learning (CL) methods is to prioritize stability by penalizing changes in parameters crucial to old tasks, while allowing for plasticity in other parameters. The importance of weights for each task can be determined either explicitly through learning a task-specific mask during training (e.g., parameter isolation-based approaches) or implicitly by introducing a regularization term (e.g., regularization-based approaches). However, all these methods assume that the importance of weights for each task is unknown prior to data exposure. In this paper, we propose ScrollNet as a scrolling neural network for continual learning. ScrollNet can be seen as a dynamic network that assigns the ranking of weight importance for each task before data exposure, thus achieving a more favorable stability-plasticity tradeoff during sequential task learning by reassigning this ranking for different tasks. Additionally, we demonstrate that ScrollNet can be combined with various CL methods, including regularization-based and replay-based approaches. Experimental results on CIFAR100 and TinyImagenet datasets show the effectiveness of our proposed method. |
|
|
Address |
Paris; France; October 2023 |
|
|
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 |
ICCVW |
|
|
Notes |
LAMP |
Approved |
no |
|
|
Call Number |
Admin @ si @ WWW2023 |
Serial |
3945 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Stephane Ayache; Jun Wan; Meysam Madadi; Umut Guçlu; Xavier Baro |
|
|
Title |
Inpainting and Denoising Challenges |
Type |
Book Whole |
|
Year |
2019 |
Publication |
The Springer Series on Challenges in Machine Learning |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising, restoration, super-resolution, or inpainting.
Inpainting and Denoising Challenges comprises recent efforts dealing with image and video inpainting tasks. This includes winning solutions to the ChaLearn Looking at People inpainting and denoising challenges: human pose recovery, video de-captioning and fingerprint restoration.
This volume starts with a wide review on image denoising, retracing and comparing various methods from the pioneer signal processing methods, to machine learning approaches with sparse and low-rank models, and recent deep learning architectures with autoencoders and variants. The following chapters present results from the Challenge, including three competition tasks at WCCI and ECML 2018. The top best approaches submitted by participants are described, showing interesting contributions and innovating methods. The last two chapters propose novel contributions and highlight new applications that benefit from image/video inpainting. |
|
|
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; no menciona |
Approved |
no |
|
|
Call Number |
Admin @ si @ EAW2019 |
Serial |
3398 |
|
Permanent link to this record |
|
|
|
|
Author |
Vishwesh Pillai; Pranav Mehar; Manisha Das; Deep Gupta; Petia Radeva |
|
|
Title |
Integrated Hierarchical and Flat Classifiers for Food Image Classification using Epistemic Uncertainty |
Type |
Conference Article |
|
Year |
2022 |
Publication |
IEEE International Conference on Signal Processing and Communications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
The problem of food image recognition is an essential one in today’s context because health conditions such as diabetes, obesity, and heart disease require constant monitoring of a person’s diet. To automate this process, several models are available to recognize food images. Due to a considerable number of unique food dishes and various cuisines, a traditional flat classifier ceases to perform well. To address this issue, prediction schemes consisting of both flat and hierarchical classifiers, with the analysis of epistemic uncertainty are used to switch between the classifiers. However, the accuracy of the predictions made using epistemic uncertainty data remains considerably low. Therefore, this paper presents a prediction scheme using three different threshold criteria that helps to increase the accuracy of epistemic uncertainty predictions. The performance of the proposed method is demonstrated using several experiments performed on the MAFood-121 dataset. The experimental results validate the proposal performance and show that the proposed threshold criteria help to increase the overall accuracy of the predictions by correctly classifying the uncertainty distribution of the samples. |
|
|
Address |
Bangalore; India; July 2022 |
|
|
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 |
SPCOM |
|
|
Notes |
MILAB; no menciona |
Approved |
no |
|
|
Call Number |
Admin @ si @ PMD2022 |
Serial |
3796 |
|
Permanent link to this record |
|
|
|
|
Author |
Arash Akbarinia; C. Alejandro Parraga |
|
|
Title |
Colour Constancy Beyond the Classical Receptive Field |
Type |
Journal Article |
|
Year |
2018 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
|
|
Volume |
40 |
Issue |
9 |
Pages |
2081 - 2094 |
|
|
Keywords |
|
|
|
Abstract |
The problem of removing illuminant variations to preserve the colours of objects (colour constancy) has already been solved by the human brain using mechanisms that rely largely on centre-surround computations of local contrast. In this paper we adopt some of these biological solutions described by long known physiological findings into a simple, fully automatic, functional model (termed Adaptive Surround Modulation or ASM). In ASM, the size of a visual neuron's receptive field (RF) as well as the relationship with its surround varies according to the local contrast within the stimulus, which in turn determines the nature of the centre-surround normalisation of cortical neurons higher up in the processing chain. We modelled colour constancy by means of two overlapping asymmetric Gaussian kernels whose sizes are adapted based on the contrast of the surround pixels, resembling the change of RF size. We simulated the contrast-dependent surround modulation by weighting the contribution of each Gaussian according to the centre-surround contrast. In the end, we obtained an estimation of the illuminant from the set of the most activated RFs' outputs. Our results on three single-illuminant and one multi-illuminant benchmark datasets show that ASM is highly competitive against the state-of-the-art and it even outperforms learning-based algorithms in one case. Moreover, the robustness of our model is more tangible if we consider that our results were obtained using the same parameters for all datasets, that is, mimicking how the human visual system operates. These results might provide an insight on how dynamical adaptation mechanisms contribute to make object's colours appear constant to us. |
|
|
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 |
NEUROBIT; 600.068; 600.072 |
Approved |
no |
|
|
Call Number |
Admin @ si @ AkP2018a |
Serial |
2990 |
|
Permanent link to this record |
|
|
|
|
Author |
Gemma Sanchez; Josep Llados; Enric Marti |
|
|
Title |
Segmentation and analysis of linial texture in plans |
Type |
Conference Article |
|
Year |
1997 |
Publication |
Intelligence Artificielle et Complexité. |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Structural Texture, Voronoi, Hierarchical Clustering, String Matching. |
|
|
Abstract |
The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph. |
|
|
Address |
Paris, France |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
Paris |
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AERFAI |
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ SLM1997 |
Serial |
1649 |
|
Permanent link to this record |
|
|
|
|
Author |
Santiago Segui; Laura Igual; Jordi Vitria |
|
|
Title |
Bagged One Class Classifiers in the Presence of Outliers |
Type |
Journal Article |
|
Year |
2013 |
Publication |
International Journal of Pattern Recognition and Artificial Intelligence |
Abbreviated Journal |
IJPRAI |
|
|
Volume |
27 |
Issue |
5 |
Pages |
1350014-1350035 |
|
|
Keywords |
One-class Classifier; Ensemble Methods; Bagging and Outliers |
|
|
Abstract |
The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In
this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
|
|
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 |
OR; 600.046;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ SIV2013 |
Serial |
2256 |
|
Permanent link to this record |
|
|
|
|
Author |
Mikhail Mozerov; Joost Van de Weijer |
|
|
Title |
Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering |
Type |
Journal Article |
|
Year |
2015 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
|
|
Volume |
24 |
Issue |
12 |
Pages |
5842-5853 |
|
|
Keywords |
|
|
|
Abstract |
The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results. |
|
|
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 |
1057-7149 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
LAMP; 600.079;ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ MoW2015b |
Serial |
2689 |
|
Permanent link to this record |
|
|
|
|
Author |
Olivier Penacchio; C. Alejandro Parraga |
|
|
Title |
What is the best criterion for an efficient design of retinal photoreceptor mosaics? |
Type |
Journal Article |
|
Year |
2011 |
Publication |
Perception |
Abbreviated Journal |
PER |
|
|
Volume |
40 |
Issue |
|
Pages |
197 |
|
|
Keywords |
|
|
|
Abstract |
The proportions of L, M and S photoreceptors in the primate retina are arguably determined by evolutionary pressure and the statistics of the visual environment. Two information theory-based approaches have been recently proposed for explaining the asymmetrical spatial densities of photoreceptors in humans. In the first approach Garrigan et al (2010 PLoS ONE 6 e1000677), a model for computing the information transmitted by cone arrays which considers the differential blurring produced by the long-wavelength accommodation of the eye’s lens is proposed. Their results explain the sparsity of S-cones but the optimum depends weakly on the L:M cone ratio. In the second approach (Penacchio et al, 2010 Perception 39 ECVP Supplement, 101), we show that human cone arrays make the visual representation scale-invariant, allowing the total entropy of the signal to be preserved while decreasing individual neurons’ entropy in further retinotopic representations. This criterion provides a thorough description of the distribution of L:M cone ratios and does not depend on differential blurring of the signal by the lens. Here, we investigate the similarities and differences of both approaches when applied to the same database. Our results support a 2-criteria optimization in the space of cone ratios whose components are arguably important and mostly unrelated.
[This work was partially funded by projects TIN2010-21771-C02-1 and Consolider-Ingenio 2010-CSD2007-00018 from the Spanish MICINN. CAP was funded by grant RYC-2007-00484] |
|
|
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 |
CIC |
Approved |
no |
|
|
Call Number |
Admin @ si @ PeP2011a |
Serial |
1719 |
|
Permanent link to this record |
|
|
|
|
Author |
Sophie Wuerger; Kaida Xiao; Chenyang Fu; Dimosthenis Karatzas |
|
|
Title |
Colour-opponent mechanisms are not affected by age-related chromatic sensitivity changes |
Type |
Journal Article |
|
Year |
2010 |
Publication |
Ophthalmic and Physiological Optics |
Abbreviated Journal |
OPO |
|
|
Volume |
30 |
Issue |
5 |
Pages |
635-659 |
|
|
Keywords |
|
|
|
Abstract |
The purpose of this study was to assess whether age-related chromatic sensitivity changes are associated with corresponding changes in hue perception in a large sample of colour-normal observers over a wide age range (n = 185; age range: 18-75 years). In these observers we determined both the sensitivity along the protan, deutan and tritan line; and settings for the four unique hues, from which the characteristics of the higher-order colour mechanisms can be derived. We found a significant decrease in chromatic sensitivity due to ageing, in particular along the tritan line. From the unique hue settings we derived the cone weightings associated with the colour mechanisms that are at equilibrium for the four unique hues. We found that the relative cone weightings (w(L) /w(M) and w(L) /w(S)) associated with the unique hues were independent of age. Our results are consistent with previous findings that the unique hues are rather constant with age while chromatic sensitivity declines. They also provide evidence in favour of the hypothesis that higher-order colour mechanisms are equipped with flexible cone weightings, as opposed to fixed weights. The mechanism underlying this compensation is still poorly understood. |
|
|
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 |
DAG; IF: 1.259 |
Approved |
no |
|
|
Call Number |
Admin @ si @ WXF2010 |
Serial |
1826 |
|
Permanent link to this record |
|
|
|
|
Author |
Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva |
|
|
Title |
Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation |
Type |
Conference Article |
|
Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
|
|
|
Volume |
14 |
Issue |
3 |
Pages |
496-503 |
|
|
Keywords |
|
|
|
Abstract |
The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%. |
|
|
Address |
Toronto, Canada |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-642-23625-9 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
MICCAI |
|
|
Notes |
MILAB;HuPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ HGE2011 |
Serial |
1769 |
|
Permanent link to this record |
|
|
|
|
Author |
Mohamed Ramzy Ibrahim; Robert Benavente; Felipe Lumbreras; Daniel Ponsa |
|
|
Title |
3DRRDB: Super Resolution of Multiple Remote Sensing Images using 3D Residual in Residual Dense Blocks |
Type |
Conference Article |
|
Year |
2022 |
Publication |
CVPR 2022 Workshop on IEEE Perception Beyond the Visible Spectrum workshop series (PBVS, 18th Edition) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Training; Solid modeling; Three-dimensional displays; PSNR; Convolution; Superresolution; Pattern recognition |
|
|
Abstract |
The rapid advancement of Deep Convolutional Neural Networks helped in solving many remote sensing problems, especially the problems of super-resolution. However, most state-of-the-art methods focus more on Single Image Super-Resolution neglecting Multi-Image Super-Resolution. In this work, a new proposed 3D Residual in Residual Dense Blocks model (3DRRDB) focuses on remote sensing Multi-Image Super-Resolution for two different single spectral bands. The proposed 3DRRDB model explores the idea of 3D convolution layers in deeply connected Dense Blocks and the effect of local and global residual connections with residual scaling in Multi-Image Super-Resolution. The model tested on the Proba-V challenge dataset shows a significant improvement above the current state-of-the-art models scoring a Corrected Peak Signal to Noise Ratio (cPSNR) of 48.79 dB and 50.83 dB for Near Infrared (NIR) and RED Bands respectively. Moreover, the proposed 3DRRDB model scores a Corrected Structural Similarity Index Measure (cSSIM) of 0.9865 and 0.9909 for NIR and RED bands respectively. |
|
|
Address |
New Orleans, USA; 19 June 2022 |
|
|
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 |
CVPRW |
|
|
Notes |
MSIAU; 600.130 |
Approved |
no |
|
|
Call Number |
Admin @ si @ IBL2022 |
Serial |
3693 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
|
|
Title |
Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance |
Type |
Book Chapter |
|
Year |
2012 |
Publication |
Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence |
Abbreviated Journal |
|
|
|
Volume |
384 |
Issue |
3 |
Pages |
87-95 |
|
|
Keywords |
|
|
|
Abstract |
The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally. |
|
|
Address |
|
|
|
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 |
1860-949X |
ISBN |
978-3-642-24033-1 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ BFR2012 |
Serial |
2062 |
|
Permanent link to this record |