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Author |
Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie |
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Title |
Inferring the Performance of Medical Imaging Algorithms |
Type |
Conference Article |
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Year |
2011 |
Publication  |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
6854 |
Issue |
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Pages |
520-528 |
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Keywords |
Validation, Statistical Inference, Medical Imaging Algorithms. |
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Abstract |
Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
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Address |
Sevilla |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
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CAIP |
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Notes |
IAM; ADAS |
Approved |
no |
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Call Number |
IAM @ iam @ HGR2011 |
Serial |
1676 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
Space Variant Representations for Mobile Platform Vision Applications |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
6855 |
Issue |
II |
Pages |
146-154 |
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Abstract |
The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow. |
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Address |
Seville, Spain |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
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ISSN |
0302-9743 |
ISBN |
978-3-642-23677-8 |
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Conference |
CAIP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
NaS2011; ADAS @ adas @ |
Serial |
1686 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
An inference model for analyzing termination conditions of Evolutionary Algorithms |
Type |
Conference Article |
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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 |
216-225 |
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Keywords |
Evolutionary Computation Convergence, Termination Conditions, Statistical Inference |
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Abstract |
In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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Address |
Lleida, Catalonia (Spain) |
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Corporate Author |
Associació Catalana Intel·ligència Artificial |
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ISBN |
978-1-60750-841-0 |
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Conference |
CCIA |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ RGG2011a |
Serial |
1677 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Depth of Valleys Accumulation Algorithm for Object Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
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Volume |
1 |
Issue |
1 |
Pages |
71-80 |
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Keywords |
Object Recognition, Object Region Identification, Image Analysis, Image Processing |
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Abstract |
This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas. |
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Address |
Lleida |
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ISBN |
978-1-60750-841-0 |
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Area |
800 |
Expedition |
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Conference |
CCIA |
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Notes |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011b |
Serial |
1699 |
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Author |
Xavier Perez Sala; Cecilio Angulo; Sergio Escalera |
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Title |
Biologically Inspired Turn Control in Robot Navigation |
Type |
Conference Article |
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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 |
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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. |
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Address |
Lleida |
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ISBN |
978-1-60750-841-0 |
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Conference |
CCIA |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ PAE2011a |
Serial |
1753 |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
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Title |
Virtual Worlds and Active Learning for Human Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th International Conference on Multimodal Interaction |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
393-400 |
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Keywords |
Pedestrian Detection; Human detection; Virtual; Domain Adaptation; Active Learning |
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Abstract |
Image based human detection is of paramount interest due to its potential applications in fields such as advanced driving assistance, surveillance and media analysis. However, even detecting non-occluded standing humans remains a challenge of intensive research. The most promising human detectors rely on classifiers developed in the discriminative paradigm, i.e., trained with labelled samples. However, labeling is a manual intensive step, 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, some authors 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 rendered images, i.e., using 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, or similar ones. Accordingly, in this paper we address the challenge of using a virtual world for gathering (while playing a videogame) a large amount of automatically labelled samples (virtual humans and background) and then training a classifier that performs equal, in real-world images, than the one obtained by equally training from manually labelled real-world samples. For doing that, we cast the problem as one of 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 propose a non-standard active learning technique. Therefore, ultimately our human model is learnt by the combination of virtual and real world labelled samples (Fig. 1), which has not been done before. We present quantitative results showing that this approach is valid. |
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Address |
Alicante, Spain |
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Publisher |
ACM DL |
Place of Publication |
New York, NY, USA, USA |
Editor |
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Language |
English |
Summary Language |
English |
Original Title |
Virtual Worlds and Active Learning for Human Detection |
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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 |
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ISBN |
978-1-4503-0641-6 |
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Expedition |
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Conference |
ICMI |
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Notes |
ADAS |
Approved |
yes |
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Call Number |
ADAS @ adas @ VLP2011a |
Serial |
1683 |
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Author |
Ruth Aylett; Ginevra Castellano; Bogdan Raducanu; Ana Paiva; Marc Hanheide |
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Title |
Long-term socially perceptive and interactive robot companions: challenges and future perspectives |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th International Conference on Multimodal Interaction |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
323-326 |
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Keywords |
human-robot interaction, multimodal interaction, social robotics |
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Abstract |
This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours. |
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Address |
Alicante |
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Corporate Author |
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Thesis |
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Publisher |
ACM |
Place of Publication |
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Original Title |
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Series Editor |
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ISBN |
978-1-4503-0641-6 |
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Conference |
ICMI |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ ACR2011 |
Serial |
1888 |
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Author |
Koen E.A. van de Sande; Jasper Uilings; Theo Gevers; Arnold Smeulders |
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Title |
Segmentation as Selective Search for Object Recognition |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1879-1886 |
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Abstract |
For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt segmentation as a selective search by reconsidering segmentation: We propose to generate many approximate locations over few and precise object delineations because (1) an object whose location is never generated can not be recognised and (2) appearance and immediate nearby context are most effective for object recognition. Our method is class-independent and is shown to cover 96.7% of all objects in the Pascal VOC 2007 test set using only 1,536 locations per image. Our selective search enables the use of the more expensive bag-of-words method which we use to substantially improve the state-of-the-art by up to 8.5% for 8 out of 20 classes on the Pascal VOC 2010 detection challenge. |
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Address |
Barcelona |
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Series Editor |
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Series Volume |
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Edition |
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ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
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Expedition |
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Conference |
ICCV |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ SUG2011 |
Serial |
1780 |
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Author |
E. Serradell; Adriana Romero; R. Leta; Carlo Gatta; Francesc Moreno-Noguer |
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Title |
Simultaneous Correspondence and Non-Rigid 3D Reconstruction of the Coronary Tree from Single X-Ray Images |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
850-857 |
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Abstract |
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Address |
Barcelona |
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Conference |
ICCV |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ SRL2011 |
Serial |
1803 |
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Author |
Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez; Xavier Roca |
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Title |
A Selective Spatio-Temporal Interest Point Detector for Human Action Recognition in Complex Scenes |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1776-1783 |
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Keywords |
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Abstract |
Recent progress in the field of human action recognition points towards the use of Spatio-Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this paper we present a new approach for STIP detection by applying surround suppression combined with local and temporal constraints. Our method is significantly different from existing STIP detectors and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-visual words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on existing benchmark datasets, and more challenging datasets of complex scenes, validate our approach and show state-of-the-art performance. |
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Address |
Barcelona |
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Corporate Author |
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Edition |
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ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
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Expedition |
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Conference |
ICCV |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ CHM2011 |
Serial |
1811 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
Correspondence Free Registration through a Point-to-Model Distance Minimization |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
2150-2157 |
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Keywords |
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Abstract |
This paper presents a novel formulation, which derives in a smooth minimization problem, to tackle the rigid registration between a given point set and a model set. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, we propose to describe the model set by means of an implicit representation. It allows a new definition of the registration error, which works beyond the point level representation. Moreover, it could be used in a gradient-based optimization framework. The proposed approach consists of two stages. Firstly, a novel formulation is proposed that relates the registration parameters with the distance between the model and data set. Secondly, the registration parameters are obtained by means of the Levengberg-Marquardt algorithm. Experimental results and comparisons with state of the art show the validity of the proposed framework. |
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Address |
Barcelona |
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ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
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Expedition |
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Conference |
ICCV |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RoS2011b; ADAS @ adas @ |
Serial |
1832 |
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Author |
Shida Beigpour; Joost Van de Weijer |
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Title |
Object Recoloring Based on Intrinsic Image Estimation |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference in Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
327 - 334 |
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Abstract |
Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods. |
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Address |
Barcelona |
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Corporate Author |
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Series Editor |
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Edition |
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ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
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Expedition |
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Conference |
ICCV |
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Notes |
CIC |
Approved |
no |
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Call Number |
Admin @ si @ BeW2011 |
Serial |
1781 |
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Author |
Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
The IIIA30 MObile Robot Object Recognition Datset |
Type |
Conference Article |
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Year |
2011 |
Publication |
11th Portuguese Robotics Open |
Abbreviated Journal |
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Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. |
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Lisboa |
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Robotica |
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RV;ADAS |
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Admin @ si @ RAV2011 |
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1777 |
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Author |
Xavier Perez Sala; Cecilio Angulo; Sergio Escalera |
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Biologically Inspired Path Execution Using SURF Flow in Robot Navigation |
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2011 |
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11th International Work Conference on Artificial Neural Networks |
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II |
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581--588 |
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An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo. |
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Malaga |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-21497-4 |
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IWANN |
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HuPBA;MILAB |
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Admin @ si @ PAE2011b |
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1773 |
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Jon Almazan; Alicia Fornes; Ernest Valveny |
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A Non-Rigid Feature Extraction Method for Shape Recognition |
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2011 |
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11th International Conference on Document Analysis and Recognition |
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987-991 |
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This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. |
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Beijing; China; September 2011 |
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978-0-7695-4520-2 |
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ICDAR |
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DAG |
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Admin @ si @ AFV2011 |
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1763 |
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