| Records |
| Author |
Arjan Gijsenij; Theo Gevers |
| Title |
Color Constancy Using Natural Image Statistics and Scene Semantics |
Type |
Journal Article |
| Year |
2011 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
33 |
Issue |
4 |
Pages |
687-698 |
| Keywords |
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| Abstract |
Existing color constancy methods are all based on specific assumptions such as the spatial and spectral characteristics of images. As a consequence, no algorithm can be considered as universal. However, with the large variety of available methods, the question is how to select the method that performs best for a specific image. To achieve selection and combining of color constancy algorithms, in this paper natural image statistics are used to identify the most important characteristics of color images. Then, based on these image characteristics, the proper color constancy algorithm (or best combination of algorithms) is selected for a specific image. To capture the image characteristics, the Weibull parameterization (e.g., grain size and contrast) is used. It is shown that the Weibull parameterization is related to the image attributes to which the used color constancy methods are sensitive. An MoG-classifier is used to learn the correlation and weighting between the Weibull-parameters and the image attributes (number of edges, amount of texture, and SNR). The output of the classifier is the selection of the best performing color constancy method for a certain image. Experimental results show a large improvement over state-of-the-art single algorithms. On a data set consisting of more than 11,000 images, an increase in color constancy performance up to 20 percent (median angular error) can be obtained compared to the best-performing single algorithm. Further, it is shown that for certain scene categories, one specific color constancy algorithm can be used instead of the classifier considering several algorithms. |
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Series Issue |
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Edition |
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| ISSN |
0162-8828 |
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Medium |
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Expedition |
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Conference |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ GiG2011 |
Serial |
1724 |
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| Author |
Albert Ali Salah; Theo Gevers; Nicu Sebe; Alessandro Vinciarelli |
| Title |
Computer Vision for Ambient Intelligence |
Type |
Journal Article |
| Year |
2011 |
Publication |
Journal of Ambient Intelligence and Smart Environments |
Abbreviated Journal |
JAISE |
| Volume |
3 |
Issue |
3 |
Pages |
187-191 |
| Keywords |
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Expedition |
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Conference |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ SGS2011a |
Serial |
1725 |
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| Author |
Arnau Ramisa; Alex Goldhoorn; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
| Title |
Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas |
Type |
Journal Article |
| Year |
2011 |
Publication |
Journal of Intelligent and Robotic Systems |
Abbreviated Journal |
JIRC |
| Volume |
64 |
Issue |
3-4 |
Pages |
625-649 |
| Keywords |
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| Abstract |
Biologically inspired homing methods, such as the Average Landmark Vector, are an interesting solution for local navigation due to its simplicity. However, usually they require a modification of the environment by placing artificial landmarks in order to work reliably. In this paper we combine the Average Landmark Vector with invariant feature points automatically detected in panoramic images to overcome this limitation. The proposed approach has been evaluated first in simulation and, as promising results are found, also in two data sets of panoramas from real world environments. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Netherlands |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0921-0296 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
RV;ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RGA2011 |
Serial |
1728 |
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| Author |
Koen E.A. van de Sande; Theo Gevers; Cees G.M. Snoek |
| Title |
Empowering Visual Categorization with the GPU |
Type |
Journal Article |
| Year |
2011 |
Publication |
IEEE Transactions on Multimedia |
Abbreviated Journal |
TMM |
| Volume |
13 |
Issue |
1 |
Pages |
60-70 |
| Keywords |
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| Abstract |
Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the trend to increase computational power in newer CPU and GPU architectures is to increase their level of parallelism, exploiting this parallelism becomes an important direction to handle the computational cost of the bag-of-words approach. When optimizing a system based on the bag-of-words approach, the goal is to minimize the time it takes to process batches of images. Additionally, we also consider power usage as an evaluation metric. In this paper, we analyze the bag-of-words model for visual categorization in terms of computational cost and identify two major bottlenecks: the quantization step and the classification step. We address these two bottlenecks by proposing two efficient algorithms for quantization and classification by exploiting the GPU hardware and the CUDA parallel programming model. The algorithms are designed to (1) keep categorization accuracy intact, (2) decompose the problem and (3) give the same numerical results. In the experiments on large scale datasets it is shown that, by using a parallel implementation on the Geforce GTX260 GPU, classifying unseen images is 4.8 times faster than a quad-core CPU version on the Core i7 920, while giving the exact same numerical results. In addition, we show how the algorithms can be generalized to other applications, such as text retrieval and video retrieval. Moreover, when the obtained speedup is used to process extra video frames in a video retrieval benchmark, the accuracy of visual categorization is improved by 29%. |
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Expedition |
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Conference |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ SGS2011b |
Serial |
1729 |
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| Author |
Mario Rojas; David Masip; Jordi Vitria |
| Title |
Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
371-378 |
| Keywords |
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| Abstract |
Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RMV2011a |
Serial |
1731 |
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| Author |
Lluis Pere de las Heras; Gemma Sanchez |
| Title |
And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
17-24 |
| Keywords |
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| Abstract |
This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Abbreviated Series Title |
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Edition |
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ISBN |
978-3-642-21256-7 |
Medium |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ HeS2011 |
Serial |
1736 |
| Permanent link to this record |
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| Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva |
| Title |
A Holistic Approach for the Detection of Media-Adventitia Border in IVUS |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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| Volume |
6893 |
Issue |
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Pages |
401-408 |
| Keywords |
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| Abstract |
In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm. |
| Address |
Toronto, Canada |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-23625-9 |
Medium |
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Expedition |
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Conference |
MICCAI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ CPG2011 |
Serial |
1739 |
| Permanent link to this record |
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| Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
| Title |
Saliency Estimation Using a Non-Parametric Low-Level Vision Model |
Type |
Conference Article |
| Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
433-440 |
| Keywords |
Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms |
| Abstract |
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. |
| Address |
Colorado Springs |
| Corporate Author |
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Thesis |
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Place of Publication |
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Summary Language |
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Original Title |
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Series Issue |
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Edition |
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| ISSN |
1063-6919 |
ISBN |
978-1-4577-0394-2 |
Medium |
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Conference |
CVPR |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ MVO2011 |
Serial |
1757 |
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| Author |
Xavier Perez Sala; Cecilio Angulo; Sergio Escalera |
| Title |
Biologically Inspired Turn Control in Robot Navigation |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
187-196 |
| Keywords |
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| Abstract |
An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot. |
| Address |
Lleida |
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Summary Language |
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Edition |
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ISBN |
978-1-60750-841-0 |
Medium |
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Conference |
CCIA |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ PAE2011a |
Serial |
1753 |
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| Author |
Antonio Hernandez; Carlo Gatta; Laura Igual; Sergio Escalera; Petia Radeva |
| Title |
Automatic Angiography Segmentation Based on Improved Graph-cut |
Type |
Conference Article |
| Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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Pages |
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Series Title |
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Edition |
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Conference |
TICGI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ HGI2011 |
Serial |
1754 |
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| Author |
Laura Igual; Antonio Hernandez; Sergio Escalera; Miguel Reyes; Josep Moya; Joan Carles Soliva; Jordi Faquet; Oscar Vilarroya; Petia Radeva |
| Title |
Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
| Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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Pages |
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Conference |
TICGI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ IHE2011 |
Serial |
1755 |
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| Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
| Title |
Cool world: domain adaptation of virtual and real worlds for human detection using active learning |
Type |
Conference Article |
| Year |
2011 |
Publication |
NIPS Domain Adaptation Workshop: Theory and Application |
Abbreviated Journal |
NIPS-DA |
| Volume |
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Issue |
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Pages |
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| Keywords |
Pedestrian Detection; Virtual; Domain Adaptation; Active Learning |
| Abstract |
Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity. |
| Address |
Granada, Spain |
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Thesis |
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Place of Publication |
Granada, Spain |
Editor |
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| Language |
English |
Summary Language |
English |
Original Title |
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Conference |
DA-NIPS |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ VLP2011b |
Serial |
1756 |
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| Author |
Jordi Roca; A.Owen; G.Jordan; Y.Ling; C. Alejandro Parraga; A.Hurlbert |
| Title |
Inter-individual Variations in Color Naming and the Structure of 3D Color Space |
Type |
Abstract |
| Year |
2011 |
Publication |
Journal of Vision |
Abbreviated Journal |
VSS |
| Volume |
12 |
Issue |
2 |
Pages |
166 |
| Keywords |
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| Abstract |
36.307
Many everyday behavioural uses of color vision depend on color naming ability, which is neither measured nor predicted by most standardized tests of color vision, for either normal or anomalous color vision. Here we demonstrate a new method to quantify color naming ability by deriving a compact computational description of individual 3D color spaces. Methods: Individual observers underwent standardized color vision diagnostic tests (including anomaloscope testing) and a series of custom-made color naming tasks using 500 distinct color samples, either CRT stimuli (“light”-based) or Munsell chips (“surface”-based), with both forced- and free-choice color naming paradigms. For each subject, we defined his/her color solid as the set of 3D convex hulls computed for each basic color category from the relevant collection of categorised points in perceptually uniform CIELAB space. From the parameters of the convex hulls, we derived several indices to characterise the 3D structure of the color solid and its inter-individual variations. Using a reference group of 25 normal trichromats (NT), we defined the degree of normality for the shape, location and overlap of each color region, and the extent of “light”-“surface” agreement. Results: Certain features of color perception emerge from analysis of the average NT color solid, e.g.: (1) the white category is slightly shifted towards blue; and (2) the variability in category border location across NT subjects is asymmetric across color space, with least variability in the blue/green region. Comparisons between individual and average NT indices reveal specific naming “deficits”, e.g.: (1) Category volumes for white, green, brown and grey are expanded for anomalous trichromats and dichromats; and (2) the focal structure of color space is disrupted more in protanopia than other forms of anomalous color vision. The indices both capture the structure of subjective color spaces and allow us to quantify inter-individual differences in color naming ability. |
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Edition |
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| ISSN |
1534-7362 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ ROJ2011 |
Serial |
1758 |
| Permanent link to this record |
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| Author |
C. Alejandro Parraga; Jordi Roca; Maria Vanrell |
| Title |
Do Basic Colors Influence Chromatic Adaptation? |
Type |
Journal Article |
| Year |
2011 |
Publication |
Journal of Vision |
Abbreviated Journal |
VSS |
| Volume |
11 |
Issue |
11 |
Pages |
85 |
| Keywords |
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| Abstract |
Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered. |
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1534-7362 |
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Conference |
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| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ PRV2011 |
Serial |
1759 |
| Permanent link to this record |
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| Author |
Mario Rojas; David Masip; Jordi Vitria |
| Title |
Predicting Dominance Judgements Automatically: A Machine Learning Approach. |
Type |
Conference Article |
| Year |
2011 |
Publication |
IEEE International Workshop on Social Behavior Analysis |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
939-944 |
| Keywords |
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| Abstract |
The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task. |
| Address |
Santa Barbara, CA |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-1-4244-9140-7 |
Medium |
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| Area |
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Expedition |
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Conference |
SBA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RMV2011b |
Serial |
1760 |
| Permanent link to this record |
